Final Evaluation Report | Global Station for Big Data and Cybersecurity, GI-CoRE, Hokkaido University

Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education(GI-CoRE)
Hokkaido University

Final Evaluation Report

北海道大学

国際連携研究教育局

ビッグデータ・サイバーセキュリティグローバルステーション

外部評価報告書

July 2021

July 2021
2021 年 7 月

名称未設定-4 1

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Final Evaluation Report(brief version in Japanese)
外部評価報告書（日本語・概要版）

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2

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もくじ（日本語版）

はじめに •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 5
外部評価委員 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 7
外部評価委員会実地調査要領••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 8
外部評価調書の概要 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 93

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はじめに
国際連携研究教育局（GI-CoRE）は、北海道大学の強みや特色を活かした国際連携
研究教育の推進と、部局が独自に進める国際連携研究教育の支援を目的とし、世界トップレベルの教員を国内外及び学内から結集した総長直轄の教員組織です。
GI-CoRE 内には研究領域ごとの活動拠点である「グローバルステーション（GS）」
を置き、各 GS において、原則 5 年間の設置期間内に重点的に研究教育活動を進めています。これまでに、延べ 8 つの GS（下記※を参照）を設置し、研究活動を推進するとともに、最先端の研究成果を大学院教育などに還元してきました。
GI-CoRE では、GS の設置期間満了を迎える年度に、各 GS でのこれまでの活動を振り返るとともに、今後、より強固かつ持続可能な研究教育体制を確立していくため、
国内外の有識者により構成される外部評価委員会において、評価を実施することとしています。
この外部評価報告書は、2020 年 7 月に実施したビッグデータ・サイバーセキュリティ GS（GSB）の自己点検成果報告書及び外部評価結果を一冊に収録した、いわば GSBの研究教育活動の集大成です。
なお、ビッグデータ・サイバーセキュリティ GS は設置期間満了に伴い、情報科学研究院に定着化し、新たに「GI-CoRE 協力拠点」として認定を受けたビッグデータとIoT に関する協同センターとして、2021 年 4 月以降も GI-CoRE と連携しながら研究
教育活動を継続しています。
本学では、外部評価結果を踏まえ、より充実した研究教育活動を実践していくこと
により、世界の課題解決に貢献していきたいと考えております。

北海道大学 国際連携研究教育局長
寳 金 清 博※これまでに設置したグローバルステーション（GS）
GS 名

設置期間
（年度）

主な学内連携部局等

量子医理工学2014～2019

医学研究院、大学病院ほか

人獣共通感染症

2014～2019

人獣共通感染症国際共同研究所、獣医学研究院

食水土資源

2015～2019

農学研究院ほか

ソフトマター2016～2020

先端生命科学研究院ほか

ビッグデータ・サイバーセキュリティ

2016～2020

情報科学研究院ほか

北極域研究2016～2020

北極域研究センターほか

バイオサーフィス創薬

2019～2023

薬学研究院ほか

先住民・文化的多様性研究

2021～2025

アイヌ・先住民研究センターほか

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国際連携研究教育局 (GI‐CoRE)
ビッグデータ・サイバーセキュリティグローバルステーション
外部評価委員*国立情報学研究所

コンテンツ科学研究系

高野

明彦

教授

オーストラリア

ニューサウスウェールズ州政府データ解析研究所
イアン・オッパーマン CEO

アメリカ合衆国

南カリフォルニア大学

スヴェン・ケーニヒ

教授

*委員長

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国際連携研究教育局 (GI‐CoRE)
ビッグデータ・サイバーセキュリティ
グローバルステーション
外部評価委員会実地調査要領

１．調査日程令和 2（2020）年 7 月 7 日（火）２．詳細スケジュール
7 月 7 日（火）日本時間
日本時間
8:30～8:55

次第

豪州

米国

米国

#1 開会宣言（大鐘教授）

9:30～

16:30～

19:30～

参加者紹介（吉岡 GS 長）

9:55

16:55

19:55

#2 GSB 全体の活動報告（吉岡 GS

9:55～

16:55～

19:55～

長）

10:50

17:50

20:50

11:00～

18:00～

21:00～

11:30

18:30

21:30

開会挨拶（笠原総長代行・GI-CoRE
局長代行）

記念撮影
8:55～9:50
9:50～

休憩

10:00
10:00～
10:30#3 UMass Amherst ﾕﾆｯﾄから
※注１

活動報告

（ｼｭﾛﾓ ｼﾞﾙﾊﾞｰｽﾀｲﾝ教

授）
10:30～#4 UTS ﾕﾆｯﾄから活動報告

11:30-

18:30～

21:30～

10:55（ｴﾘｯｸ ﾃﾞｭﾄｷｴｳﾞｨｯﾁ教授）

11:55

18:55

21:55

10:55～

休憩
12:05～

19:05～

22:05～

12:40

19:40

22:40

12:40～

19:40～

22:40～

13:25

21:25

23:25

13:35～

21:35～

23:35～

14:00

22:00

00:00

11:05
11:05～#5 評価委員ヒアリング

11:40
11:40-#6 評価委員ディスカッション

12:25
12:25～

休憩

12:35
12:35～

#7 総括

13:00

注１：アメリカ東部との時差の都合により、本セッション終了後 UMass 代表は 10：30（日本時間）で退出予定。

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国際連携研究教育局 (GI‐CoRE)
ビッグデータ・サイバーセキュリティグローバルステーション
外部評価調書の概要（参考和訳）

総合評価：Ａ（評価コメント）
重要で時宜を得たトピックに関する国際研究と教育の実現を目指す「ビッグデータ・サイバー
セキュリティグローバルステーション（GSB）」の全体的な開発の方向性を高く評価します。GSBの研究課題：ビッグデータ、サイバーセキュリティ、IoTは、学際的な研究を考える上で重要で横断的な視点を与えてくれます。
このGSBの開発の方向性は、日本政府が第5次科学技術基本計画で設定した研究と教育の方向性を十分に配慮したものとなっています。GSBの活動により得られた重要な資産は、人事交流、共同
研究プロジェクト、共同での教材制作を通じてGSBの目的を非常に積極的に支援する研究グループ
として、マサチューセッツ大学アマースト校とシドニー工科大学という優れた国際パートナー大学を得たことであります。この国際連携の強さは、国際的な研究パートナーシップの質と、個々の研究者が行う連携のための取り組みにより決まります。さまざまな分野でのGSBの研究貢献は、GSBの国際連携が国際レベルに達していることを示しています。
国境を越えた共同研究を成功させるためには、研究プロジェクトのために世界の一線級の専門家を集めることがますます重要になっています。同時に、学生が世界レベルの最高の教師から学ぶことができるのは理想的です。 GSBの枠組みは、これらの研究と教育の目的を促進するように設計されています。国際的な研究協力を中心とした研究者と学生の国際交流を促進することは、
国際的な研究人材を育成するために重要です。このアプローチを通じて、GSBは学際的な研究分野をカバーする国際的な大学院教育カリキュラムを構築しました。
GSBにおける最も重要な目的は、特定の国際共同研究プロジェクトの質を向上させることよりは、学際的な研究分野をバランスよくカバーする大学院教育の国際化であるように思われます。 海外の外部評価委員からのスコアが比較的低いのは、このGSBの目的が明確に伝えられていなかったためと思われます。GSBの活動を通じて、大学院教育のカリキュラムがどのように変化したかについての、より詳細な報告が求められます。
GSBの価値を高めるには、その研究活動を、得られた新しい知識による影響だけでなく、グロー
バルな課題解決にどのように影響するかを示す「影響力の経路」を示す必要があります。 そのために、研究成果を社会的または世界的な影響に変換するためのメカニズムについて考えることが必要です。様々な研究課題の領域を含めることは、GSBの活動を拡大していくためには、潜在的に非常に有力ですが、その研究成果は上記の「影響の経路」を尊重する必要があります。たとえば、世界がデータとデジタル接続にますます依存するようになるにつれて、ますます複雑になるシス
テムのサイバーセキュリティは重要なトピックになるでしょう。
GI-CoRE の GSB プログラムに対する全体的な評価は「Excellent（A）」です。国際的な共同研究と教育を実施するために必要な制度と組織体制の確立に成功し、新しい国際大学院コースのカリ
キュラムの再設計につながりました。外部評価委員一同は、GSB の継続を心から推奨します。

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Final Evaluation Report(original version in English)
外部評価報告書（英語・オリジナル版）

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Contents
Foreword •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 15
External Evaluation Committee••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 17
Schedule of the External Evaluation Committee •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 21
Results of the Evaluation Committee ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 23
Research Progress Report (2016-2020) ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 49
References ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••145

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Foreword
Hokkaido University established the Global Institution for Collaborative Research and
Education (GI-CoRE) as a faculty organization under the direct control of the President thatbrings together world-class researchers from around the world and within the University. It
aims to promote international collaborative research and education that leverages the
University’s strengths and distinctive features as well as to provide support for international
collaborative research and education promoted by faculties and centers, respectively.
Under the GI-CoRE system, a research and education hub known as a Global Station (GS) is
implemented for each research field. GSs have a finite implementation period of five (5) years
in principle to conduct intensive research and education activities. Thus far, eight (8) GSs in
total (see * below) have been implemented to further develop research activities and contributethe resulting cutting-edge research outcomes to graduate school education.
In the final year of the GI-CoRE project period, a Final Evaluation is conducted by the External
Evaluation Committee composed of global experts outside Hokkaido University for each GS
to not only review GS activities from past years but also build a stronger and more sustainable
research and education system in the future.
This Final Evaluation Report contains the Research Progress Report of GS for Big Data andCybersecurity (GSB) conducted in July 2020 and the evaluation results. This report is acompilation of the research and education activities of GSB.
After the implementation period, GSB project was transitioned into Faculty of Information
Science and Technology and it was certified as Collaborative Center for Big data and IoT, oneof the “GI-CoRE Cooperating Hubs,” to continue research and education activities incooperation with GI-CoRE after April 2021.
Hokkaido University remains committed to continuing its efforts to contribute to resolving
global issues by conducting advanced research and education activities based on evaluation
results.

Kiyohiro Houkin,
Director,
Global Institution for Collaborative Research and Education (GI-CoRE),
Hokkaido University(President, Hokkaido University)

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*The Global Stations (GSs) implemented thus far.
Name of the GS
Quantum Medical Science and

Implementation
2014–2019

Engineering
Zoonosis Control

Main Internal Affiliation）
Period (FY）

FacultyofMedicine,

University

Hospital, and others
2014–2019

International Institute for Zoonosis
Control and Faculty of Veterinary
Medicine

Food, Land and Water Resources

2015–2019

Research Faculty of Agriculture andothersSoft Matter

2016–2020

Faculty of Advanced Life Science andothersBig Data and Cybersecurity

2016–2020

Faculty of Information Science andTechnology and others

Arctic Research

2016–2020

Arctic Research Center and others

Biosurfaces and Drug Discovery

2019–2023

Faculty of Pharmaceutical Sciences andothersIndigenous Studies and Cultural

2021-2025

Diversity

Center for Ainu and Indigenous Studies
and others

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Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education (GI‐CoRE)
External Evaluation Committee*Professor Akihiko Takano,
Digital Content and Media Sciences Research Division, National Institute of Informatics (NII)(Japan)Ian Oppermann,
NSW Government Chief Data Scientist and CEO, NSW Data
Analytics Centre (DAC) (Australia)
Professor Sven Koenig,
Computer Science Department, University of Southern California (USC) (United States)*Chair17

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令和２年３月31日
国立大学法人北海道大学
局長職務代理 殿

国際連携研究教育局

職員の任命について（回答）

令和２年３月２３日付け海大国連第４−２号で依頼のありましたこのことについて，下記のとおり回答します。
記■□

承諾いたします。
職名・氏名

教授・高野

明彦

任命期間

令和２年４月１日〜令和３年３月３１日

承諾いたしかねます。

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Attachment

Letter of Acceptance
25/03/ 2020

To Acting Director Kasahara Masanori of the Global Institution for Collaborative
Research and Education (GI-CoRE), the National University Corporation Hokkaido
University.

I hereby accept my appointment to serve as a member of the External Evaluation
Committee for the Global Station for Big Data and Cybersecurity at the Global Institution
for Collaborative Research and Education (GI-CoRE), Hokkaido University.
Period: From 1 April 2020 to 31 March 2021

Signature
Dr. Ian Oppermann

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Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education(GI‐CoRE)
Schedule of the External Evaluation Committee

1. Date of Implementation
Tuesday, July 7, 2020
2. Investigation Schedule
Tuesday, July 7, 2020
JST

Session

AEST

PST

EST

8:308:55#1 Opening (Prof. Ogane)
9:30Members Introduction (Prof. Yoshioka,
9:55
GSB Director)
Opening Remarks (Acting President, Acting
Director of GI-CoRE)
Photo Session

16:30- 19:3016:55 19:55

8:559:50#2 Explanation about GSB activities
by Prof. Masaharu Yoshioka, GSB Director

09:5510:50

16:55- 19:5517:50 20:50

9:5010:00

Break

10:0010:30#3 Explanation about GSB activities@UMass by PI*(Prof. Shlomo Zilberstein)

11:0011:30

18:00- 21:0018:30 21:30

10:3010:55#4 Explanation about GSB activities@UTS by PI(Prof. Eryk Dutkiewicz)

11:3011:55

18:30- 21:3018:55 21:55

10:5511:05

Break

11:0511:40#5 Interview by Evaluation Committee
members

12:0512:40

19:05- 22:0519:40 22:40

11:4012:25#6 Discussion by Evaluation Committee
members

12:4013:25

19:40- 22:4021:25 23:25

12:2512:35

Break

12:3513:00#7 Wrap-up

13:3514:00

21:35- 23:3522:00 00:00

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Results of the Evaluation Committee

Evaluation Committee

Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education (GI‐CoRE)
Hokkaido University
October 202023

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Summary Report
Professor Sven Koenig, University of Southern California (United States)
Dr. Ian Oppermann, NSW Data Analytics Centre (Australia)
Professor Akihiko Takano, National Institute of Informatics (Japan)
Comprehensive Evaluation

S / A / B / C / D (circle one)

We applaud the overall development direction of the Global Station for Big Data and Cybersecurity(GSB) , which pursues multi-national research and education on important and timely topics. GSB’s
Focus: Big Data, Cybersecurity, and Internet of Things are important orthogonal perspectives fordevising interdisciplinary research.
The GSB is well aware of the direction of research and education set by the Japanese government in
the 5th Science and Technology Basic Plan. The primary asset of GSB is its excellent international
partner universities, the University of Massachusetts at Amherst and the University of Technology
Sydney, with research groups that support the objectives of GSB very actively via personnel exchanges,
joint research projects, and course material production. The strengths of collaboration are the quality ofinternational research partnerships and the collaboration efforts of individual researchers. GSB's
research contributions in various fields have proven to be at the international level.
Bringing together top experts from around the world for research projects is increasingly importantfor successful cross-border collaborative research. At the same time, it is ideal for students to be able tolearn from the best teachers in the world. The GSB scheme is designed to facilitate these research andeducational objectives. Promoting international exchange of researchers and students centered oninternational research collaboration is important for developing international research human resources.
Through this approach, GSB has built an international graduate education curriculum that covers crossdisciplinary research areas.
The GSB's priority seems to be the internationalization of graduate education, which covers
interdisciplinary research areas in a balanced manner, rather than improving the quality of specificinternational collaborative research projects. The relatively low score of reviewers from overseas seems
to be due to the fact that the aim of this GSB was not clearly communicated. More detailed reports
should be given on how the curriculum of graduate education has changed through the activities of
GSB.
To increase the value of GSB, we need a pathway of influence to show how research and activities
affect global challenges beyond improving the state of global knowledge. Mechanisms need to be25

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planned to transform research outcomes into social or global impacts. Mixing focal areas is potentiallyvery powerful in order to expand GSB activity, but the outcome must anticipate the above pathway of
influence. For example, as the world becomes increasingly dependent on data and digital connectivity,
cybersecurity in increasingly complex systems would become an important topic.
The overall evaluation of the GI-CoRE program GSB is excellent (A). It has successfully establishedthe system and framework necessary to conduct international cooperative research and education, andlead to redesigning the new international graduate course curriculum. The reviewers heartfully
recommend the continuation of GSB.

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Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education (GI‐CoRE)
Final Evaluation
External Evaluation Committee Member Name:

Akihiko Takano

Choose one of the five Evaluation Ratings options below as explained by the Evaluation Explanation for each
Evaluation Item on the form.
Evaluation

Evaluation Explanation

Ratings
S

Achieved outcomes surpassed the original plan (Outstanding)A

Good progress has been maintained and expected outcomes have been achieved(Excellent)

B

Most expected outcomes have been achieved with some slight delays (Good)C

Although certain outcomes were achieved, overall results were insufficient (Satisfactory)D

No expected outcomes were achieved (Unsatisfactory)I.

Research1.

Has construction of an international research and education center capable of attracting outstanding researchers

from around the world (including from HU) been achieved?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
The Global Station for Big Data and Cybersecurity (GSB) has successfully carried out international research andeducation projects with a focus on key research areas. It is made up of HU's strong research group and its
outstanding international partner universities. Many internationally recognized researchers in multiple fields are
involved. GSB supports these international cooperation through active exchange of researchers, collaborative
research projects, and preparation of course materials.
Specific points(Outstanding points)
Although the major affiliated universities are limited to the University of Massachusetts Amherst (UMA) and the
University of Technology Sydney (UTS), the quality of the joint project is very high and has won numerous
publications, patents and awards.

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(Suggestions for improvement)
The collaborations are limited within the research group or within the specific discipline. It would be moreproductive if the greater collaborations between different research groups or different disciplines happen.

2.

Is world-leading cutting-edge international cooperative research underway?

Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Collaboration in the field of IoT is underway with the UTS team, known as one of the leading research centers for
IoT. Collaboration with UMA on big data is also underway. Many international symposiums were held by GSB topromote new collaborations. Some of them have succeeded in obtaining competitive funding.
These research efforts on hot themes in the field of ICT provide a forum for discussion on the reorganization of
HU's Graduate School of Information Science and Technology.
Specific points(Outstanding points)
HU cross-appointment of UMA and UTS researchers is very effective in deepening research cooperation byexchanging a series of lectures on specific research topics and co-authoring joint treatises through daily discussions.
(Suggestions for improvement)
Under the current threat of COVID-19, it is necessary to devise the new scheme for promoting international
research collaboration.

3.

Are research outcomes from GI-CoRE being actively utilized to solve social issues?

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Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Most of the collaborations hosted by GSB are still at the academic research level and are not ready to provide
solutions to real social problems.
Specific points(Outstanding points)
A good example is the "Japanese and Australian Wagyu Traceability" project, which is the result of joint research
between HU and UTS. However, it is still in the process of "solving" social problems.
(Suggestions for improvement)
Under the current situation with COVID-19, the work on infection modelling is especially relevant to the importantsocial issues.

II.

Education

1. Is the educational system and curriculum designed to help develop researchers who possess specialized
knowledge and are capable of working internationally?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
In the focused field of research in GSB, there are many international exchanges of researcher in both directions, andactively organized seminars and symposiums together. It definitely helps to develop human resources forinternational research activities.
Specific points(Outstanding points)
By conducting international collaborative research at GSB, students will acquire the scientific communication skills
in English that are essential for participating in the international research community.

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(Suggestions for improvement)
If all courses in GSB are given in English, it is even more effective for students to be accustomed to communication
in English.

2. Is the educational framework designed to develop human resources who possess expert knowledge andcapable of working internationally in the fields of big data, IoT and cybersecurity?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
There are many research visits in both directions, and actively organized seminars and symposiums together. The
experience of these collaborations is crucial to develop IT professionals in big data science, IoT and cybersecurity.
Specific points(Outstanding points)
By conducting international collaborative research at GSB, students will acquire scientific communication skills in
English that are essential for participating in the international research community.
(Suggestions for improvement)
It is too early to assess whether the proposed educational framework is effective in developing human resources
with expertise and abilities in the field. A much longer term evaluation is suitable for it.

III.

Establishment of Framework

Are the necessary systems and frameworks being established in order to conduct international cooperative researchand education?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
The success of collaborations with UTS and UMA to date seems to be highly dependent on specific researchers.
This is unavoidable at first, but in the long run it needs to be transformed into systematic collaboration.

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Specific points(Outstanding points)
Active joint research activities such as joint thesis writing and joint seminars have been reported. It is also recordedthat many researchers visited each other and gave lectures to achieve this.
(Suggestions for Improvement)
Look for collaborative research partners other than UTS and UMA and envision long-term collaborative research ina wider range of fields. The long-term interaction of postdoctoral researchers may help strengthen these research
relationships.

IV.

Overall Evaluation

GSB's focus on big data, IoT and cybersecurity is very timely and relevant. Plans to address this challengewith international collaborative research and a new educational curriculum are also effective.
GSB's foremost assets are its outstanding international partner universities, the University of
Massachusetts Amherst and the University of Technology Sydney. Both schools have strong researchgroups on GSB research themes, and many joint research and symposiums have been organized throughcross-appointments and joint research with them.
The GSB's vision of inviting the best researchers from around the world to create the ideal education andresearch curriculum is worth the effort. It not only promotes the purpose of GSB research and education,
but also provides important cultural experiences to those involved.
The quality of collaborative research at GSB has reached the international level in various fields, asevidenced by the list of co-authored papers published and the content of the joint symposium held.

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32

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Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education (GI‐CoRE)
Final Evaluation
External Evaluation Committee Member Name:

Ian Oppermann

Choose one of the five Evaluation Ratings options below as explained by the Evaluation Explanation for each
Evaluation Item on the form.
Evaluation

Evaluation Explanation

Ratings
S

Achieved outcomes surpassed the original plan (Outstanding)A

Good progress has been maintained and expected outcomes have been achieved(Excellent)

B

Most expected outcomes have been achieved with some slight delays (Good)C

Although certain outcomes were achieved, overall results were insufficient (Satisfactory)D

No expected outcomes were achieved (Unsatisfactory)I.

Research1.

Has construction of an international research and education center capable of attracting outstanding researchers

from around the world (including from HU) been achieved?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
The Global Station has identified areas for research focus which are important, aligned to the Nationally andinternationally important goals and which are well aligned with the timeframes for meaningful research impact.
The researchers involved are internationally recognized and represent multiple disciplines.
A minor concern however is that there are only 2 main research partners outside of HU.
A greater concern is that the researchers are not working across teams. Rather they remain in their areas of
discipline focus.
As an example, the inclusion of a hospital and medical researchers in an ICT focused program provides a great deal

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of opportunity to extend the traditional reach of ICT research. There is little evidence of multi-disciplinary researchor of teams referring to, or building on, research outputs of other parts of the Global Station.
Specific points(Outstanding points)Interesting and relevant outcomes being addressed in the form of major societal goals.

High quality and committed partners in the form of UTS and UMA(Suggestions for improvement)2.



Need for greater collaboration between discipline areas and between groups

Need for broader scope of collaboration beyond existing partners at UTS and UMANeed for more multi-disciplinary, collaborative publications in international journals

Is world-leading cutting-edge international cooperative research underway?

Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Collaboration is clearly underway in IoT in particular with the UTS team.
Collaboration is underway with UMA in data.
Specific points(Outstanding points)
The work with UTS in particular shows research which addresses important, real world problems in a multi-disciplinarymanner. The Wagu tagging and extension to seafood shows real promise linking IoT and blockchain to real world needs.
Grants have been awarded and seminars run.

Work on cyber security has not demonstrated the same level of focus.
(Suggestions for improvement)
There is not a great deal of evidence for IoT activity outside of the UTS collaboration.
There is also not a great deal of evidence that the medical / bio informatics research spans more than a limited
domain. The infection modelling may draw on population level data but does not seem to connect to the otherdomains at UMA or at UTS.

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The fields of research seem quite narrow. The international journal publications are highly dependent on a modest
number of individual contributors from the Global Station.
There is a need for more multi-disciplinary, collaborative publications in international journals spanning more of thescope of the Global Station.
More international journals papers would strengthen this area.

3.

Are research outcomes from GI-CoRE being actively utilized to solve social issues?

Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
The activity associated with grant writing, holding seminars and publishing papers are all traditional activities ofuniversities and academics. There is little evidence that these “activities” lead to “outcomes”.
Specific points(Outstanding points)
Work on infection modelling will help governments around the world better understand the spread of disease, but
this work must still clearly connect to the goals of the Global Station and would benefit from great crossdisciplinary collaboration.
(Suggestions for improvement)
A pathway from a seminar or publication to the advancement of one of the goals of the Global Station must be
described and measured. Examples may include that the work of the Global Station has:a. influenced government policy,
b. influenced government legislation,c. led to new research initiatives by others outside of the Global Station research partners
d. created new businesses opportunities (beyond patents)
e. raised public awareness of issues, or provided high quality information to the general public on theseissuesf.

Trained researchers who have then created impact

g. Development and sharing of infrastructure which can be used by others outside of the Global Station
research partners

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The success stories for the Global Station need to be clearly described and published. These are the sort of stories
which the public or Government Minister’s would understand.

II.

Education

1. Is the educational system and curriculum designed to help develop researchers who possess specialized
knowledge and are capable of working internationally?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
There is good evidence of exchange research visits, seminars and joint publications. Travel restrictions makecollaboration more difficult. The Global Station was clearly active before COVID impacted travel.
Specific points(Outstanding points)
Topical seminars, research visits, joint publications, patents applications are all evidence of creating frameworks orcontributing to the current state of global knowledge.

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(Suggestions for improvement)
Greater mixing of disciplines is required. In particular, the opportunity to take advantage of IoT, big data and healthrepresents a powerful opportunity.
Greater exposure to international conferences and seminars in English may also help with the internationalization of
graduates.

2. Is the educational framework designed to develop human resources who possess expert knowledge andcapable of working internationally in the fields of big data, IoT and cybersecurity?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
There is clear evidence of international contributions to Big Data, IoT through publications, seminars, lectures.
There is less evidence of contributions to Cyber security. Whilst there are public seminars and lectures, thehigh-quality international journals for cybersecurity are missing. Even conference papers are less prominent that theother domains.
Specific points(Outstanding points)
Evidence of activity which builds and shares expert knowledge
The collaborative project with UTS on Wagu beef tracking is a good example of addressing a real word problem
using multiple skills and discipline areas.
(Suggestions for improvement)
More evidence of expert contributions to the state of world knowledge (journal papers, patents, major awards)
would improve the results in this area.
Whilst not helpful for the assessment in 2020, the longer-term ability to follow the careers of graduates of the
Global Station would provide a very good indicator if assessed 5 or 10 years from now.

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III.

Establishment of Framework

Are the necessary systems and frameworks being established in order to conduct international cooperative researchand education?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Collaboration with UTS and UMA has clearly been established. This collaboration does seem dependent on
individual researchers. Whilst this is understandable, it represents a possible weakness to longer term or more
systematic collaboration. Longer term post-doctoral study periods may help cement these research relationships.

Specific points(Outstanding points)
Clear evidence of joint publications and seminars.
Evidence of multiple research visits and of individuals visiting multiple times.
(Suggestions for Improvement)
Developing plans for longer term collaboration, greater mixing of discipline areas and bringing more partners
together (beyond UTS and UMA).

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IV.

Overall Evaluation

The Global Station has clearly demonstrated evidence of collaboration in the target areas.
The focus of the Global station is good, and the topics are relevant for society.
The strength of the collaboration is the quality of the international research partnerships and the commitment tocollaborate from individual researchers. There is evidence of contributions at an international level in a diverse
number of areas.
The areas for improvement of the collaboration include:The need for impact pathways to show how the research and activities will impact the global challenges
beyond improving the state of global knowledge. The mechanisms to translate research outputs into societal
or global impact need to be mapped out. There are many ways this could be demonstrated, but clear impact
pathways need to be described. Existing research activities and any new research activities can then be
tested against these impact pathways.



Limited collaboration between disciplines. Mixing the area of focus is potentially very powerful. Incentives
should be developed to encourage multi-disciplinary actives. These should be aligned with the impact
pathways / impact mapping described above.

The focus of the research areas. Research challenges addressed by the Global Station should be chosen as
clear problems / sub-problems which need to be overcome to achieve societal impact. Taking the UN
Sustainable Development Goals as an example of outcomes to be achieved by 2030, sub-problems aredescribed which must be addressed in order to achieve the goals, as are measurable indicators of progress. A
version of these outcomes frameworks could be described for Japan and the research of the Global Stationaligned against them.



Limited focus on Cyber security. The relatively low focus on cyber security represents an opportunity for
future activity. As the world becomes increasingly dependent on data and digital connectivity, cyber securityof increasingly complex systems becomes ever more important.



Increasing the level of partnership. Going beyond the existing key research collaborators will help to extend
the longevity of international collaboration. Developing plans for longer term collaboration, greater mixingof discipline areas and bringing more partners together (beyond those within UTS and UMA) would all
potentially strengthen the quality of the work of the global station.

Limited number of success stories. Capturing successes in a way which is meaningful for the generalpublic, politicians and administrators will help build the reputation of the Global Station as a successful
activity.

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40

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Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education (GI‐CoRE)
Final Evaluation
External Evaluation Committee Member Name:

Sven Koenig

Choose one of the five Evaluation Ratings options below as explained by the Evaluation Explanation for each
Evaluation Item on the form.
Evaluation

Evaluation Explanation

Ratings
S

Achieved outcomes surpassed the original plan (Outstanding)A

Good progress has been maintained and expected outcomes have been achieved(Excellent)

B

Most expected outcomes have been achieved with some slight delays (Good)C

Although certain outcomes were achieved, overall results were insufficient (Satisfactory)D

No expected outcomes were achieved (Unsatisfactory)I.

Research1.

Has construction of an international research and education center capable of attracting outstanding researchers

from around the world (including from HU) been achieved?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Specific points(Outstanding points)
Strengths: GSB consists of strong research groups at Hokkaido University and its excellent international partner
universities that support the objectives of GSB very actively via personnel exchanges, joint research projects, andcourse material production. The research strengths of GSB are reflected in quantitative indicators, such as many
publications, awards, and patents as well as an increasing number of joint publications. The presentation of research
results in the GSB-organized international symposia helps to advertise the research results.

(Suggestions for improvement)

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Weaknesses: The research topics could be more focused, the international collaborations could be intensified (forexample, via systematic student exchanges on a larger scale), the number of joint publications between researchgroups at Hokkaido University and at least one international partner university of GSB could be increased, and thejoint supervision of students by faculty members from different universities still needs to be institutionalized.
Student and faculty surveys could help with future evaluations.

2.

Is world-leading cutting-edge international cooperative research underway?

Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Specific points(Outstanding points)
Strengths: GSB got a good start with interesting projects on Big Data and the Internet of Things. It remained unclear
to which degree the available data-processing speeds and network throughputs (which resulted in records held by
GSB research groups) are utilized by other GSB research groups but they might be enablers for some research on
Big Data and the Internet of Things.

(Suggestions for improvement)
Weaknesses: More focus in the tackled research topics might increase the visibility of the research further (whichmight be difficult to achieve given the breadth of the research interests of the participating researchers, which
include several topics more at the periphery of Big Data and the Internet of Things, such as evolutionary biology,
genomics, cognitive sciences, geometry/topology, and nanotechnology/materials), the resulting research topics
could be linked more tightly, and the fusion of research directions in Big Data, Cybersecurity, and the Internet ofThings has yet to be achieved (for example, via large research projects that combine more than two research areas
with expertise present in GSB).

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3.

Are research outcomes from GI-CoRE being actively utilized to solve social issues?

Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Specific points(Outstanding points)
Strengths: GSB pursues some research projects with clear societal impact, such as the “detecting bias on news
websites” project in conjunction with the University of Massachusetts at Amherst and the “Wagyu beef” project inconjunction with the University of Technology Sydney.
(Suggestions for improvement)
Weaknesses: The societal impact of the research could be increased further by collaborating more with domestic andoverseas industries as well as putting more emphasis on the societal impact of research projects.

II.

Education

1. Is the educational system and curriculum designed to help develop researchers who possess specialized
knowledge and are capable of working internationally?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Specific points(Outstanding points)
Strengths: The research and educational activities of GSB have strong international components. The upcoming
cotutelle program as well as internships with governmental research institutions and companies are great ideas.
E-learning does not only support the international education component but also helps to educate working adults.
(Suggestions for improvement)
Weaknesses: The contact between students taking an e-learning course and its lecturer could be intensified (toincrease the cultural component of the education), and all courses could be offered in English (to help GSB students

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to get even more quickly used to communication in English). Student and faculty surveys could help with futureevaluations.

2. Is the educational framework designed to develop human resources who possess expert knowledge andcapable of working internationally in the fields of big data, IoT and cybersecurity?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
N/A since the evaluation material was not sufficiently focused on the curricula of the GSB programs on Big Data,
Cybersecurity, and the Internet of Things. For example, it remained unclear exactly which topics are taught and towhich degree project-based learning is supported.
Specific points(Outstanding points)
Strengths: The collaborations with the University of Massachusetts at Amherst on Big Data and the University ofTechnology Sydney on Cybersecurity and the Internet of Things are strong.
(Suggestions for improvement)
Weaknesses: Not all educational tracks are strongly related to Big Data, Cybersecurity, and the Internet of Things.
For example, Bioengineering/Bioinformatics provides one of many application areas for research on Big Data, but awhole curriculum on them does not help to develop human resources on Big Data, Cybersecurity, and the Internet ofThings.

III.

Establishment of Framework

Are the necessary systems and frameworks being established in order to conduct international cooperative researchand education?
Evaluation Results and Reasons(Your Evaluation Results)
S / A / B / C / D (circle one)
(Reasons)
Specific points(Outstanding points)

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Strengths: The faculty members of Hokkaido University can concentrate fully on GSB activities. The international
co-operations are supported well, for example, by English-speaking staff members.
(Suggestions for Improvement)
Weaknesses: The school has been restructured although I am not able to sufficiently judge the impact of thereorganization.

IV.

Overall Evaluation

I applaud the overall development direction of the Global Station for Big Data and Cybersecurity (GSB), which
pursues multi-national research and education on important and timely topics. The name of GSB is slightly
misleading since the global station is broader than its name implies, for example, also covers the Internet of Things
as well as additional topics (such as Singularity Theory or Bioengineering). I thus recommend that the name bechanged to the Global Station for Big Data, Cybersecurity, and the Internet of Things.
GSB is very responsive to the directions for research and education desired by the Japanese government in the Fifth
Science and Technology Basic Plan. One asset of GSB is its excellent international partner universities, theUniversity of Massachusetts at Amherst and the University of Technology Sydney, with research groups that support
the objectives of GSB very actively via personnel exchanges, joint research projects, and course material
production. (The roles of Temple University and some of the many organizational units at Hokkaido University areless clear.) Collaborative research, including across borders, is the future of research since it becomes more andmore important to bring top experts from around the world together for research projects. Similarly, students shouldbe able to learn from the best teachers from around the world. The GSB activities do not only further these researchand educational objectives of GSB but also provide an important cultural experience for the people involved. The
upcoming cotutelle program is also a great idea for these reasons. All current GSB activities have been well thought
out and are supported well, for example, by English-speaking staff members.
The breadth of the GSB activities in the past years is impressive (ranging from giving lectures at conferences and to
the public to organizing international symposia and “exchange idea” seminars). For example, restructuring a school
is not easy and involves a massive amount of effort. The GSB activities have resulted in lots of successes, which arereflected in quantitative indicators, such as a large number of publications, awards, and patents as well as anincreasing number of joint publications. Overall, I feel that GSB got off to a very successful start. In the following, I
will therefore focus on its future.
The GSB activities and their outcomes have resulted in valuable experience for the GSB leadership on how toachieve the objectives of GSB best. Now is the time for the GSB leadership to evaluate which activities worked

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well. This requires comprehensive (quantitative) data, which were sparse in the self- assessment report (forexample, in terms of the job placement of graduated students or the number of joint publications between researchgroups at Hokkaido University and at least one international partner university of GSB) but fortunately moreabundant in the slides presented at the meeting with the evaluation committee. Additional data would be valuablefor the GSB leadership when making decisions on future GSB activities, such as the results of student surveys (bothbefore and after graduation) about which GSB activities were considered most valuable by them – and similar
faculty surveys of GSB personnel at Hokkaido University and the involved research groups at the international
partner universities.
Once the GSB leadership has evaluated the various current GSB activities, it might want to concentrate in the futureon those activities that provide the most value and link them more tightly. For example, it might be helpful to think
about the best way of systematically starting and fostering multi-national research collaborations and provide evenmore incentives for them, which would also provide a desirable boost in the number of joint publications between
research groups at Hokkaido University and at least one international partner university of GSB. Multi-national
research collaborations require either longer visits (from faculty members or students) or regular teleconferences.
Often, visits of Ph.D. students to other research groups are a good way of starting research collaborations. Thus, it
could make sense to start a formal GSB-funded exchange program of Ph.D. students on a larger scale, for example,
with visits of 3 months with the possibility of longer stays for those students whose visits resulted in interesting
research. Students will tend to join research groups that are similar to the research groups they are part of at theirhome universities but joining research groups with different but complementary expertise can also result ininteresting collaborations. However, the students might not go for such opportunities unless they are incentivized to
do so. Attracting students from international partner universities to spend longer periods of time at Hokkaido
University needs to be incentivized as well since the different language might be viewed by some students as an
obstacle. Furthermore, the joint supervision of students by faculty members from different universities still needs to
be institutionalized.
It might be helpful to consider how the contact between students taking an e-learning course and its lecturer can beintensified, both for GSB courses on video that were developed by the international partner universities and for
lectures that are given in person by visiting researchers. While listening to international lecturers is helpful forstudents, additional contact one-on-one or in small groups with them would be desirable, even if it were via zoom
(or similar software) for GSB courses on video.
Similarly, the contact between personnel from Hokkaido University and the international partner universities could
be increased via joint educational activities, such as co-developing courses or co-teaching their lectures (viarecording videos or lecturing live on zoom).
It might be helpful to consider whether more focus in the tackled research topics might increase the visibility of theresearch further, whether the resulting research topics can be linked more tightly, and how to fuse the research
directions in Big Data, Cybersecurity, and the Internet of Things (for example, via large research projects that46

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combine more than two research areas with expertise present in GSB). Similarly, increasing the collaboration withdomestic and overseas industries as well as putting more emphasis on the societal impact of research projects could
increase the impact of the research further, as the successful Wagyu beef project of GSB suggests.
It might also make sense to consider how to make GSB stand out even more in Japan, perhaps by pursuing more
extreme activities. For example, individual lectures in English are common at Japanese universities but GSB stands
out since longer lecture series in English around the same topic are uncommon. Thus, it is commendable thatstudents can satisfy all credit requirements with courses taught in English. I might have misunderstood theself-assessment report, but it appears that some courses are still taught in Japanese. Since it makes sense to offersome lectures in English, one could be more extreme by offering all courses in English (including those given by
faculty members from Hokkaido University) to help GSB students to get even more quickly used to communication
in English. This change could also attract more foreign students to GSB, including visiting students from theinternational partner universities, which might result in even more research collaborations with the international
partner universities. Similarly, since it makes sense to offer subjects from the humanities (including law) to GSB
students, one could be more extreme by offering additional subjects from the humanities (beyond patent law andethics) or co-teaching subjects with lecturers from the humanities.
All of the activities suggested above require additional funding, part of which should be provided by Hokkaido
University (perhaps with some support by the international partner universities) and part of it could result from adesirable expansion of the amount of external funding received for GSB research projects (as well as teaching andstudent-exchange activities).

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48

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Global Station for Big Data and Cybersecurity
Global Institution for Collaborative Research and Education(GI‐CoRE)
Hokkaido Univeristy
Research Progress Report(Project Period: Academic Year 2016‐2020)

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50

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Contents
Ⅰ. Overview ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 53
Ⅱ. Budget ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 55
Ⅲ. Result Details ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 56
１. Research ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 56
1.1 Objective ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 56
1.2 Progress and future development ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 58
a. Status of research activities ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 58
b. Research implementation system ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 64
c. Hosting of overseas faculty members ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 67
d. Current research achievements ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 70
e. Utilization and dissemination of research achievements ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 102
f.

Issues in conducting research, their solutions and future development ꞏꞏꞏꞏꞏꞏꞏꞏ 102

２. Education (International Graduate School) ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 103
2.1 Objective ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 103
2.2 Progress and future development ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 105
a. Education implementation structure (organization) ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 105
b. Education implementation structure (system) ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 107
c. Admission of students ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 108
d. Educational content and methods ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 108
e. Outcomes of education ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 111

３. Establishment of Framework ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 112
3.1 Operating and administrative structure ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 112
3.2 Hosting structure, environment improvement and future vision ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 114

Appendix ꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏꞏ 116

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52

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I. Overview
1. Global station name: Big Data and Cybersecurity
2. Period: FY 2016 – FY 2020 (5 years)
3. Purpose and objective
To promote advanced international collaborative education and research, a new station Global Station for Big
Data and Cybersecurity (hereinafter “GSB”) was established in the Global Institution for Collaborative
Research and Education (hereinafter “GI-CoRE”) in FY 2016 by bringing together faculty members (mainly
from the Graduate School of Information Science and Technology, the Faculty of Science, University Hospital,
and the Information Initiative Center) involved in big data science (big data + data science), the Internet ofThings (IoT) and cybersecurity and by cooperating with top-class universities around the world. This global
station was launched to serve as a basis to reorganize the Graduate School of Information Science andTechnology in order to enhance practical education programs related to big data science, IoT and cybersecurity
for students that include working adults and to develop IT professionals who can play an active role in a futureoriented world.
4. Necessity and urgency
In this project, an international collaborative research hub for big data science, cybersecurity and IoT has
been formed to promote collaborative research on a global level. In addition to international collaboration, theglobal station also promotes interdisciplinary collaboration to tackle urgent research topics, such as clinicalbioinformatics, based on support from different departments. To meet an increasing need for international higher
education in these fields, it is important to promptly create a research hub to support such educational programs.
Especially in the fields of big data science and cybersecurity, there is a qualitative and quantitative shortage ofJapanese researchers and engineers who are active internationally. Accordingly, educators and researchers fromoverseas are in demand as collaborative partners.
5. Originality and novelty
Big data science, cybersecurity and IoT are recognized as important technologies that support the informationsociety of the future. These technologies are also expected to create new innovation based on interdisciplinary
collaboration. Furthermore, there is a strong demand for advanced education and research programs to support
such technologies.
Under these circumstances, Hokkaido University has established a research and education hub for big data
science, cybersecurity and IoT. Aiming to activate education and research in these three fields, this hub
collaborates not only with well-known overseas educational and research institutes but also with domestic
companies in these fields.
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In FY 2019, the previous Graduate School of Information Science and Technology was reorganized into the
Faculty of Information Science and Technology and the new Graduate School of Information Science andTechnology. The former is a research organization to which faculty members of the previous Graduate Schoolof Information Science and Technology belong, and the latter is an organization to provide education of
information science and technology through collaboration with members from the Faculty of Information
Science and Technology and other faculties of the University. At the new Graduate School of Information
Science and Technology, an international supervisor system that also envisions a cotutelle program wasestablished, allowing researchers with cross-appointments from the University of Massachusetts Amherst(UMass Amherst) and the University of Technology, Sydney (UTS) to serve as co-supervisors. Researchers withcross-appointments also provide international collaborative informatics subjects. The reorganization was
intended to prepare new educational programs and develop global-minded individuals who can be active in theworld through international collaboration and cooperation among multiple departments. This has allowed forthe formation and globalization of an educational and research hub to create future industries and new values
toward social transformation, as described in Japan’s Fifth Science and Technology Basic Plan.

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II. Budget
Unit: 1,000 JPY
Category

FY 2018

FY 2019

0

1,509

2,947

6,782

5,000

16,238

11,713

10,5286,705

9,956*

10,02048,922

0

2,624

1,972

4,578

5,650

14,82440,23972,29140,32830,03133,094215,983

51,952

86,952

51,952

51,34753,764295,967

Personnel cost

Total

Administrative cost*
Travel expenses for
invited overseas
GSB members for
short visit
Operating andresearch cost

Total

FY 2017(for researchers fromoverseas)

GI-CoRE
establishmentof framework

FY 2020

FY 2016(projected)*Including rent for invited overseas GSB member

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III. Result Details
1. Research
1.1 Objective
To realize “Hokkaido University Contributing Towards the Resolution of Global Issues,” the vision of the
Future Strategy for the 150th Anniversary of Hokkaido University proposed in August 2014, several global
stations have been established in GI-CoRE under the direct control of the President as global brain circulation
centers to develop the next-generation human resources. These global stations aim to promote advanced
international collaborative research with first-class education and research units overseas and to establish
international graduate schools.
Since its foundation in 1876, Hokkaido University has pursued four basic philosophies: “Frontier Spirit,”
which leads to taking on the challenges of the times and paving the way forward; “Global Perspectives,” which
help promote cultural and social exchanges with the people of the world; “All-round Education,” with the aimof cultivating a well-rounded character and a high level of intelligence; and “Practical Learning,” which
focuses on putting the University’s research results into practice in order to benefit society. These are not justphilosophies but have led to specific strengths and achievements, such as the establishment of “Nitobe College”
to foster leaders who are aware of themselves as Japanese in the international community and the productionof a Nobel Prize winner in chemistry.
However, Japan is facing rapid changes in society, such as the sharply declining birthrate, an aging
population, globalization, and the rise of emerging countries. In an age when it is required to make changes
aimed at a vibrant society to enable sustainable development, national universities need to carry out university
reforms in response to the demands of society, such as the development of individuals who lead change andthe creation of innovation. Based on the government’s strategy for Japan’s revitalization and recommendations
by the Education Rebuilding Implementation Council, and to transform into a leading national university thatmeets the needs of society, Hokkaido University has decided to advance reforms aimed at “contributing
towards the resolution of global issues.” This will be implemented under the leadership of the President by
combining the University’s wisdom and collective effort, utilizing the strengths of practical research and fieldresearch and organically driving great development.
To realize the vision, Hokkaido University has plotted five specific strategies as pillars of functional
enhancement: (1) promotion of world-class research for the realization of a sustainable society, (2) constructionof advanced international collaborative research hubs and development of human resources for the next
generation, (3) cultivation of leading and core human resources that contribute to the development of theinternational community, (4) university-wide educational system reforms for the development of diverse
human resources based on the University’s four basic philosophies, (5) contribution to revitalizing
communities and society in Japan and elsewhere and to creating new values.
Considering the world situation, technologies advanced by information science, such as big data science,
artificial intelligence, and the Internet of Things (IoT), have been introduced in all fields. In the information

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science filed, a wide range of research and development projects are being carried out toward the realization ofa social system that is friendly to people and the environment and an efficient and effective social system.
Meanwhile, the situation regarding recent cyberattacks has been serious, and the damage has been increasing
rapidly. This prompted Japan to enact a basic cybersecurity bill on November 6, 2014, which clarified the
responsibilities of educational research institutions. In addition, by connecting everything to the Internet (IoT)
and acquiring new knowledge and insight from the big data obtained from the IoT devices, research anddevelopment for realizing a super smart society is spreading worldwide. The Fifth Science and Technology
Basic Plan, which was endorsed by the Cabinet on January 22, 2016, highlights the importance of fundamental
technologies involving cybersecurity, IoT system construction, big data science and artificial intelligence inefforts to create new value for the development of future industry and social transformation, which include theenhancement of competitiveness and the strategic consolidation of fundamental technologies in a “super smart
society.”
Against this backdrop, Hokkaido University established the GSB in April 2016 to create an international
collaborative research hub for big data science, cybersecurity and IoT system construction in the field of
information science, and to start research at an international level through global interuniversity collaboration.
Since there are pressing needs for international higher education in related fields for future globalization, it isvery important to collaborate with the world’s top-level universities, achieve advanced education and promotecollaborative research.
GSB aims to achieve international collaboration with prominent overseas education and research institutes
related to big data science, cybersecurity and IoT, to also collaborate with domestic companies in these domains
and to create new areas by fusing big data science and cybersecurity fields. It also aims to promote practicalresearch related to the security of medical big data and joint research on safe and secure IoT, and to establish aninternational cybersecurity research and education hub for the next generation (GSB), thereby stimulating
research on big data science and cybersecurity.
After its establishment in FY 2016 aimed at collaboration with UMass Amherst in the fields of big data
science and cybersecurity, the GSB has expanded its collaboration to start relations with UTS in the IoT andcybersecurity fields. The GSB has promoted multiple collaborative research projects to achieve world-levelresearch. GSB promotes collaborative research with overseas universities, and as a result, actively publishesinternational co-authored papers. Furthermore, in the fields of big data science, IoT research and cybersecurity
technology, GSB actively promotes keynote and invited lectures at international conferences to disseminate theresearch results achieved in this project to the world, also GSB promotes collaborative research with domestic
companies and national research institutes in the related domain, and advances industry-academia-government
collaboration.

7

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1.2 Progress and future developmenta.Status of research activities[FY 2016]
On April 1, 2016, GI-CoRE established a new global station, GSB in the field of information science related
to big data science, cybersecurity and the Internet of Things (IoT). On May 16 and 17, an opening ceremonyfor GSB and a forum entitled “Forum for the 21st Century Super Smart City” were held. The forum was attended
by Prof. Bruce Croft (Dean, College of Information and Computer Sciences) and two other professors from the
University of Massachusetts Amherst (UMass Amherst, USA), as well as Mr. Sadayuki Tsuchiya (MEXT Vice
Minister), Dr. Jun’ichi Tsujii (AIST, AIRC Director), and Dr. Richard Johnson (US NAS Board Member), in
addition to researchers from Tohoku University, Kyushu University, Keio University, Ohio University, theUniversity of British Columbia and other universities to propose the establishment of a Japan-US computational
platform.
Below is an outline of specific efforts in FY 2016, including the opening ceremony.
1. Establishment of the Global Station for Big Data and Cybersecurity (GSB)◈ Improvement of on-campus venture business laboratories and the environment for collaborative research at
GSB◈ Organization of the GSB opening ceremony and the Japan-US Academia Business Forum, an international
collaborative research conference with UMass Amherst and an international industry-academia collaboration
seminar (Hokkaido University, Sapporo)◈ Conclusion of the Memorandum of Agreement between Hokkaido University, GI-CoRE and University of
Massachusetts Amherst, College of Information and Computer Sciences (CICS)◈ Researcher with a cross-appointment from UMass Amherst (one associate professor)◈ Employment of GSB researchers (post-doctors, research assistants)
2. Start of international collaborative research on big data science and cybersecurity◈ A visit to UMass Amherst by GSB faculty members (two professors, one associate professor, one assistantprofessor) for a collaborative research meeting◈ Round-table conference among those involved in industry, academia and government from Japan and theUnited States toward international industry-academia-government collaboration
3. Investigation and preparation for the establishment of the new Graduate School of Information Scienceand Technology◈ Examination of collaborative education with overseas universities, development of curricula and preparation
for credit transfer◈ Development of undergraduate curricula in collaboration with enPIT2 (educational program forcybersecurity-related field)◈ Overseas dispatch of related faculty members for the development of curricula related to cybersecurity
August: University of Tampere, Finland (one professor)
8

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January: Macquarie University and the University of Technology, Sydney, Australia (2 professors)
March: Temple University, US (one professor, one associate professor)
March: UMass Amherst, US (two professors)◈ Lectures related to big data science, cybersecurity and IoT
February: University of Technology, Sydney, Australia (two lecturers)
March: University of Technology, Sydney, Australia (three professors)
The above activities in FY 2016 were aimed at the launch of GSB and the start of practical collaborative
research with UMass Amherst’s College of Information and Computer Sciences (CICS), a partner of GSB. At
the same time, it was necessary to improve the environment for the smooth implementation of such activities.
As indicated above, GSB was established on April 1 as scheduled and the opening ceremony, related workshops
and international conferences were held with the cooperation of related researchers and officers in Japan andoverseas. At the same time, an MoA was newly concluded between CICS and GI-CoRE, and based on the MoA,
international collaborative research was started mainly by big data science researchers.
[FY 2017]
To further promote international collaborative research, which began in FY 2016, in addition to UMass
Amherst GSB started collaboration with UTS and prepared to expand the globalization of education andresearch activities. With the aim of reorganizing the Graduate School of Information Science and Technology,
in addition to the above-mentioned international collaboration, GSB also promoted interdepartmental
collaboration within the University and designed international collaborative subjects with researchers withcross-appointments from UMass Amherst and UTS. Furthermore, GSB conducted research and development
on a medical big data system for the creation of clinical bioinformatics aiming at the individualization of medicalcare.
The specific circumstances for these efforts are as follows:
1. Preparation for forming an international university network and expanding the globalization of
educational and research activities
In FY 2017, GSB conducted research and development on big data science in collaboration with UMass
Amherst, a partner university of GSB. Also, as part of this activity, two students from the Graduate School ofInformation Science and Technology were dispatched to UMass Amherst.
Furthermore, in preparation for the formation of an international university network, GSB started research on
and the development of IoT networks in collaboration with the University of Technology, Sydney (UTS,
Australia). At the same time, GSB started to design collaborative education programs with the UTS and thedevelopment of educational programs on clinical bioinformatics in collaboration with Temple University.
2. Formation of interdepartmental and international interuniversity collaboration with the aim ofreorganizing the Graduate School of Information Science and Technology
To reorganize the Graduate School of Information Science and Technology into a new system of one division
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and multiple courses in April 2019, efforts were made in FY 2017 to strengthen interdepartmental collaboration
for interdisciplinary collaborative research and education and international interuniversity collaboration for theinternationalization and globalization of research and education. Specifically, the cooperative and support
system of the entire graduate school was enhanced, and a new school system was designed with personnel
support from other departments in the University (Hokkaido University Hospital, the Faculty of Science, theInformation Initiative Center, the Research Institute for Electronic Science, and the Research Center for
Integrated Quantum Electronics) and collaboration and cooperation from the humanities fields, including the
Graduate School of Law and the Faculty of Humanities and Human Sciences. As a result, GSB developed aninterdisciplinary collaborative education program in a broad sense, including integrated education in thehumanities and sciences that is required for information science-related fields. At the same time, it designed anddeveloped international graduate education programs together with researchers with cross-appointments from
UMass Amherst, UTS and other overseas universities.
3. GSB provided international collaborative subjects in collaboration with UMass Amherst and UTS for
the Graduate School of Information Science and Technology to be newly established in FY 2019.
By introducing e-learning, these subjects can be continuously provided for lectures even after the GSB period
ends. To develop e-learning materials, preparation was made to use part of the subjects as those for the Hokkaido
Summer Institute (HSI) in 2018. This made it possible to develop effective and substantial educational programsfor individual themes such as big data science, cybersecurity and IoT. Accordingly, in FY 2017, specific subject
contents were set with overseas partner universities (UMass Amherst, UTS), and equipment necessary for elearning and software development was introduced.
4. Research and development of a medical big data system for the creation of clinical bioinformatics
aiming at individualization of medical care
A medical big data system was constructed for the creation of clinical bioinformatics throughinterdepartmental collaboration between GSB, the Graduate School of Information Science and Technology and
Hokkaido University Hospital. In FY 2017, an experimental server (prototype) was constructed to confirm theeffectiveness of the system.
Specifically, a hierarchical database was designed in the period from June to September so that different typesof information in the information system operated at Hokkaido University Hospital can be used in anonymized
and encrypted form for various research projects to create an anonymized database for clinical research(prototype).
5. Organization of international symposiums
July 10 and 11: GI-CoRE GSQ, GSB & IGM JOINT SYMPOSIUM: Quantum, Informatics, Biology &Medicine (co-hosted)

10

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[FY 2018]
Following FY 2017, the collaboration with UMass Amherst and UTS was strengthened, and preparations
were made to expand the globalization of education and research activities. To reorganize the existing Graduate
School of Information Science and Technology into an interdisciplinary education system comprised of themembers of the Faculty of Information Science and Technology, who are teaching staff of the existing graduate
school, and teaching staff of new education fields, an application to establish the new system was made and it
was approved. In addition, some of the international collaborative subjects by UMass Amherst and UTS
researchers with cross-appointments were provided at HSI. International symposiums were held and several
research projects that include the acquisition of competitive funds were started.
The specific circumstances for these efforts are as follows:
1. Formation of an international university network with GSB as the hub, together with the University of
Massachusetts and the University of Technology, Sydney◈ Regarding the University of Massachusetts, in addition to the College of Information and Computer Sciences(CICS), GSB began to consider research and education collaboration with faculty members in the Departmentof Mathematics and Statistics.
◈ GSB's activities strengthened collaboration with the University of Technology, Sydney, and the Key
Technology Partnerships (KTP) agreement was concluded in September between UTS’s Faculty ofEngineering and Information Technology and HU’s Graduate School of Information Science and Technology
to promote academic research exchanges and strategic international collaboration. Associate Professor Matteo
Convertino, a key member of GSB, made a three-week research stay at the University of Technology, Sydney
through KTP's Visiting Fellow program.
2. To establish an interdisciplinary education system beyond the existing research and education
framework, preparations were made to reorganize the Graduate School of Information Science andTechnology into the new Graduate School of Information Science and Technology with one division andmultiple courses and the Faculty of Information Science and Technology.
◈ An application was made in April 2018 to establish the new system, and it was approved in September. For
practical operation, the internal regulations of the graduate school and the faculty were prepared, and entrance
examinations were conducted.
◈ To further promote the globalization of education, it was decided to establish the new Graduate School ofInformation Science and Technology in April 2019 with the aim of expanding cutting-edge technologies, suchas big data science, security technology, and IoT technology.
◈ Members of the Faculty of Information Science and Technology, which is a research organization comprisedof faculty members of the existing Graduate School of Information Science and Technology, as well as
members of the Faculty of Science and researchers with cross-appointments participate in education at the
new Graduate School of Information Science and Technology.

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3. Development of educational programs for international collaborative informatics subjects◈ Development of educational programs for international collaborative informatics subjects provided at theGraduate School of Information Science and Technology (established in FY 2019), and preparation of elearning materials (4 subjects) as part of the subjects
E-learning materials were prepared as materials for active learning based on multiple assignments from thesubject rather than using only slides and videos.
◈ Provision of four subjects at the Hokkaido Summer Institute (HSI)
4. Organization of international symposiums
August 7 and 8: The 2nd GI-CoRE GSQ, GSB & IGM Joint Symposium: Quantum, Informatics, Biology &Medicine, Hokkaido University (co-hosted)
September 19: Twelve GSB research assistants gave presentations at a research exchange meeting.
December 20 and 21: 2018 Winter International Symposium on Big-Data, Cybersecurity and IoT (BCI 2018),
Sapporo, Japan (hosted)● Eleven GSB research assistants gave presentations.
5. International collaborative research and competitive funds◈ Professor Yoshikazu Miyanaga applied for the Fund for the Promotion of Joint International Research(Fostering Joint International Research (B)) of the Grants-in-Aid for Scientific Research (for Multi-MediaIoT based on Energy Harvest Cognitive Wireless Network, Feb, 2019 – Mar. 2021) with Lecturer Negin
Shariati (co-investigator) and Professor Xiaojing Huang (international collaborator) from UTS, and his
proposal was adopted, 13,600,000 yen.
◈ Professor Masaharu Yoshioka applied for the Grant-in-Aid for Scientific Research (B) (for Research on theanalysis and visualization of news websites stance based on the comparison among various news websites,
FY 2018 – 2021, 4 years) with Professor James Allan from UMass as a collaborative researcher, and his
proposal was adopted, 17,030,000 yen.
[FY 2019]
In 2019, the Graduate School of Information Science and Technology and the Faculty of Information Scienceand Technology were launched, and an international research and education system, including researchers withcross-appointments with UMass Amherst and UTS, was established. In addition, GSB developed seveninternational collaborative informatics subjects on big data science, security technology and IoT technology inwhich researchers with cross-appointments were also involved. GSB continued research exchanges with UMass
Amherst and UTS and acquired new competitive funds.
1. Establishment of the Graduate School of Information Science and the Faculty of Information Scienceand Technology◈ The Faculty of Information Science and Technology was established as a research organization to which
faculty members of the existing Graduate School of Information Science and Technology belong, and the1262

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new Graduate School of Information Science and Technology was established as an interdisciplinary
education organization that includes UMass Amherst and UTS researchers with cross-appointments andmembers of the Faculty of Science.
◈ At the new Graduate School of Information Science and Technology, UMass Amherst and UTS professors
with cross-appointments not only serve as co-supervisors but also provide many subjects in English. As aresult, students can satisfy credit requirements using subject provided in English only.
2. Formation of an international university network with GSB as a hub, together with UMass Amherst
and UTS◈ Associate Professor Hiroshi Tsutsui, a GSB member, made a two-week research stay at UTS through the
KTP Visiting Fellow program.
◈ Two “exchange ideas” seminars were held by overseas universities.
December 18: Ring Confidential Transaction Protocol for Blockchain, Dr. Joseph Liu, Monash University
January 9: Advanced Computing in Data Center Networks, Dr. Hong Shen, the University of Adelaide◈ Workshop
May 31 – June 2: Lefschetz Pencils and Low dimensional Topology

Host: Professor Toru Ohmoto(Graduate School of Science, Hokkaido University, GSB), Dr. Kenta Hayano (Keio University), Associate
Professor R. Inanc Baykur, invited from UMass Amherst
3. Construction of educational programs for international collaborative informatics subjects◈ To further promote the globalization of education, the new Graduate School of Information Science andTechnology was established in April with the aim of enhancing cutting-edge technologies, including big data
science, security technology and IoT technology. Seven new subjects were newly established as international
collaborative informatics subjects.
◈ Four HSI subjects were provided in collaboration with faculty members from overseas universities.
◈ One subject was provided for the Summer Institute Satellite School in collaboration with a faculty member
from an overseas university (Lecturer David Fisher, UMass Amherst).
4. Organization of international symposiums
August 8 and 9: 2019 Summer International Symposium on Big-Data, Cybersecurity and IoT, Sapporo,
Japan(hosted)● Seventeen GSB research assistants gave presentations.
August 19 – 21: International Symposium on Multimedia and Communication Technology (ISMAC 2019),
Manila, Philippines (co-hosted)
December 5 and 6: 2019 Winter International Symposium on Big-Data, Cybersecurity and IoT, Sapporo, Japan(hosted)● A poster session was held by nine GSB research assistants and four students from the Graduate School ofInformation Science and Technology who are supervised by GSB participating faculty members.
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5. International collaborative research and competitive funds
Ongoing Grants-in-Aid for Scientific Research: 2 cases● Fund for the Promotion of Joint International Research (Fostering Joint International Research (B))(Multi-Media IoT based on Energy Harvest Cognitive Wireless Network, February 2019 – March 2021),
Professor Yoshikazu Miyanaga, Faculty of Information Science and Technology, Hokkaido University(principal investigator), Lecturer Negin Shariati Moghadam (co-investigator) and Professor Xiaojing
Huang (international collaborator), University of Technology, Sydney.
● Grant-in-Aid for Scientific Research (B) (Research on analysis and visualization of news websites stancebased on the comparison among various news websites, FY 2018 – 2021, 4 years), Professor Masaharu
Yoshioka, Faculty of Information Science and Technology, Hokkaido University, Professor James Allan(collaborative researcher), UMass Amherst.
Newly acquired external funds: 1 case
● Lecturer Ying He, University of Technology, Sydney, Australian-Japan Foundation, DFAT, (Promoting
Wagyu Beef Traceability between Japan and Australia, September 2019 – June 2021), Associate Professor
Hiroshi Tsutsui (research participant), Graduate School of Information Science and Technology,
Hokkaido University, 20,000 Australian dollars.
b. Research implementation system
As of 01 April 2020, GSB consists of thirty-seven cross-appointment members as follows.
Twenty-two from Hokkaido University, six from University of Massachusetts Amherst, and nine from
University of Technology Sydney.

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As of 01 April 2020
Research Areas

Affiliated Institutions, Departments and Researcher

Description of Research

Name
College of Information and Computer Sciences·Information Retrieval

University of Massachusetts Amherst·Artificial Intelligence

Professor Shlomo ZILBERSTEIN·Machine Learning

Professor James ALLAN·Network Security

Associate Professor Mark D. CORNER·Computer Vision

Associate Professor Amir HOUMANSADR·Human Computation

Assistant Professor Subhransu MAJI

·Information Theory·Data Science

Big Data Science·Data Mining
Department of Mathematics and Statistics·Intelligent Informatics

Medical/Bio

University of Massachusetts Amherst·Design and Analysis of Algorithms

Informatics

Assistant Professor Noriyuki HAMADA·Statistical Scienceand·Multimedia Signal Processing
Faculty of Information Science and Technology·New Generation Information

Hokkaido University

Access Systems

Professor Hiroki ARIMURA·Evolutionary Biology

Professor Miki HASEYAMA·Systems Genomics

Professor Masaharu YOSHIOKA·Biodiversity

Professor Hideyuki IMAI

·Genomics

Professor Masanori SUGIMOTO·Cognitive Sciences

Professor Hidemi WATANABE·Complexity Theory

Associate Professor Naoki OSADA·Applied Mathematics andAssociate Professor Hiroyuki IIZUKA

Statistics

Associate Professor Satoshi OYAMA·Geometry and Topology

Associate Professor Yoshihiro HIROSE
Assistant Professor Charles JORDAN
Faculty of Science Hokkaido University
Professor Toru OHMOTO
Assistant Professor Michele TORIELLI
Hokkaido University Hospital·Clinical Researches

Professor Norihiro SATO
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IoT/Cybersecurity

School of Electrical and Data Engineering·5G Networks

University of Technology Sydney·IoT Networking

Professor Eryk DUTKIEWICZ·Cyber Security

Professor Ren Ping LIU·IoT Security

Professor Xiaojing HUANG·Wireless Communications

Associate Professor Mehran ABOLHASAN·Software-Defined Networks

Associate Professor Justin LIPMAN·Blockchain

Associate Professor Priyadarsi NANDA·5G and Beyond Wireless Networks

Lecturer Negin SHARIATI MOGHADAM·Communication and Network

Lecturer Ying HE

Engineering

Lecturer Beeshanga ABEWARDANA·Nanotechnology/Materials

JAYAWICKRAMA·Optical Engineering and Photonics·Electronic Devices and Equipment

Faculty of Information Science and Technology·Human Interfaces and Interactions

Hokkaido University·Human-Robot Interaction

Professor Kunimasa SAITOH·Cognitive Science

Professor Takeo OHGANE·Biocomplexity/Applied

Professor Tetsuo ONO

Complexity

Associate Professor Toshihiko NISHIMURA·Environmental System Science

Associate Professor Matteo CONVERTINO·Information Networks

Associate Professor Hiroshi TSUTSUI·Adaptive Array Antenna

Associate Professor Manabu YAMAMOTO·Robot Informatics

Assistant Professor Takashi HIKAGE·Image Processing and
Implementation·Planar Antenna·Millimeter-wave Antenna·Transmission Antenna for a Solar
Power Satellite

Beside of the above, the following two members participated GSB’s activities during the related period.
Professor Yoshikazu Miyanaga (01 April 2018 to 31 March 2020, Director of GSB), he is now Vice-presidentof Chitose Institute of Science and Technology (CIST). Professor Shin-ichi Minato (01 October 2016 to 31
March 2018), he is now professor of Department of Communications and Computers Engineering, Graduate
School of Informatics of Kyoto University currently.

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The GSB research organization chart is as below.

https://gi-core.oia.hokudai.ac.jp/gsb/members/c. Hosting of overseas faculty members[FY 2016]
1. Establishment of the Global Station for Big Data and Cybersecurity (GSB)
In addition to holding the GI-CoRE kick-off symposium and a GSB meeting, the GSB began to consider
collaboration with UTS in preparation for expanding the globalization of the station.
2. Promotion of collaborative research and education
A GSB seminar was held as a research exchange to promote collaborative research and education.
3. Number of invitees:
UMass Amherst: 3 professors, 3 assistant professors
UTS: 3 professors, 2 lecturers[FY 2017]
1. Globalization of education and research activities by forming a GSB international university network
In addition to research exchanges with UMass Amherst, collaboration began with UTS in the IoT field.
2. Promotion of collaborative research and education
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In collaboration with UMass Amherst, an educational program was developed on big data science andcybersecurity. Based on the program, an invited professor from UMass Amherst and several GSB faculty
members who belong to Hokkaido University gave a course titled “Introduction to Artificial Intelligence, Big
Data, and Cybersecurity” at the Hokkaido Summer Institute (participating overseas faculty member: Professor
James Allan, UMass Amherst).
With faculty members of Hokkaido University, three assistant professors from UMass Amherst taught patternrecognition at the Summer Institute Satellite School.
3. Number of invitees:
UMass Amherst: 1 professor, 3 assistant professors
UTS: 2 professors, 2 lecturers[FY 2018]
1. Globalization of education and research activities by forming a GSB international university network
In addition to research exchanges with UMass Amherst, the Key Technology Partnership (KTP) with UTS waslaunched.
2. Promotion of collaborative research and education
Using the video materials provided by UMass Amherst, several GSB faculty members of Hokkaido
University gave an HSI course titled “Introduction to Artificial Intelligence, Big Data, and Cybersecurity”(faculty member who provided the video materials: Lecturer David Fisher, UMass Amherst).
An educational program was developed on cybersecurity and IoT in collaboration with the University ofTechnology, Sydney. Based on the program, two courses were provided at HSI: “Cyber Security Fundamentals”(participating overseas faculty member: Associate Professor Priyadarsi Nanda, UTS) and “Introduction to
Wireless Sensor Networks and IoT” (participating overseas faculty member: Lecturer Negin Shariati, UTS)
3. Number of invitees:
UMass Amherst: None
UTS: 5 professors in total (Professor Eryk Dutkiewicz: 3 times), 2 associate professors, 2 lecturers
Others: 2018 Winter International Symposium on Big-Data, Cybersecurity and IoT (BCI 2018), Sapporo,
Japan: 1 associate professor from Chulalongkorn University, 1 professor from De La Salle University[FY 2019]
1. Globalization of education and research activities by forming a GSB international university network
In addition to the College of Information and Computer Sciences at UMass Amherst, faculty members of the
Department of Mathematics and Statistics at UMass Amherst were invited, and collaboration with UTS
continued.
2. Promotion of collaborative research and education
A faculty member from UMass Amherst and several GSB faculty members of Hokkaido University provided
an HSI course titled “Introduction to Artificial Intelligence, Big Data, and Cybersecurity” (participating
overseas faculty member: Assistant Professor Amir Houmansadr, UMass Amherst).
18

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An education program was developed on cybersecurity and IoT in collaboration with the University ofTechnology, Sydney. Based on the program, three courses were provided at HSI: “Cyber Security” (participating
overseas faculty member: Associate Professor Priyadarsi Nanda, UTS), “Software Defined Networks”(participating overseas faculty members: Associate Professor Mehran Abolhasan and Associate Professor Justin
Lipman, UTS) and “Blockchain” (participating overseas faculty member: Lecturer Ying He, UTS)
In addition to the above HSI courses, “Wireless Sensor Networks and IoT” (participating overseas faculty
members: Associate Professor Justin Lipman and Lecturer Negin Shariati, UTS) was provided as a common
subject in the Graduate School of Information Science and Technology. Two subjects for e-learning that were
HSI courses in FY 2018, “Cyber Security Fundamentals” (participating overseas faculty member: Associate
Professor Priyadarsi Nanda, UTS) and “Introduction to Wireless Sensor Networks and IoT” (participating
overseas faculty member: Lecturer Negin Shariati, UTS), were also provided as common subjects in the
Graduate School of Information Science and Technology.
In collaboration with an overseas university faculty member (Lecturer David Fisher, UMass Amherst), a
subject on information retrieval was taught at the Summer Institute Satellite School.
Assistant Professor Noriyuki Hamada, who belongs to the Department of Mathematics and Statistics at
UMass Amherst, stayed at Hokkaido University for about two months for collaborative research with Professor
Toru Ohmoto of the GSB.
3. Number of invitees:
UMass Amherst: 1 professor, 1 associate professor, 1 lecturer, 2 assistant professors
UTS: 6 professors in total (Professor Eryk Dutkiewicz: 3 times, Professor Xiaojing Huang: twice), 4 associate
professors in total (Associate Professor Justin Lipman: twice), 2 lecturers
Others: 2019 Winter International Symposium on Big-Data, Cybersecurity and IoT (BCI 2019), Sapporo,
Japan: 1 professor emeritus and 1 associate professor from Chulalongkorn University

19

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d. Current research achievements (April 2016 – March 2020)
As of March 2020 (As of March 2021)
1. International Collaborative

1-1. Featured in International Journals: #37 (#51)

Papers (Peer Reviewed): #49 (#64)

1-2. Featured in International Conference Proceedings: #12 (#13)

2. Other Publications: #353 (#471)

2-1. Featured in International Journals:#144 (#176)

2-2. Featured in International Conference Proceedings: #182 (#258)
2-3. Featured in Domestic Journals (in Japanese):
2-4. Books published:
3. Oral Presentations: #483 (#637)#23 (#32)#4 (#5)3-1. Keynote Speeches: #9, (International: #8, Japanese: #1)(#10, (International: #9, Japanese: #1))
3-2. Invited Lectures:#71, (International: #33, Japanese: #38)(#104, (International #56, Japanese #48))

3-3. Other Presentations: #403 (#523)
4. Patent Applications: #16

Patent Applications (Registered Patents): #16 (#6) (#16 (#7))
Overseas Patents: #4 (#1) (#4 (#1))
Japanese Patents: # 12 (#5) (#12 (#6))

5. Awards Received: #55 (#72)#55 (Awards at International Conferences: #22, Others: #33)(#72 (Awards at International Conferences: #34, Others: #38))

6. External Grants: #61 (#67)

Collaborative Research between HU and Overseas Members:
Others:#3 (#3)#58 (#64)

The numbers in the parentheses show the final research achievement as of March 2021. The additional items aremarked with a “ † (dagger)” in the following list.
Papers where “GI-CoRE” is stated as an affiliated institution of a Japanese or overseas researcher, or those mentioning“Hokkaido University” in the acknowledgements, are marked with a “ * (asterisk)” and the applicable author nameis underlined.
*i) Papers where “GI-CoRE” is stated as an affiliated institution*ii) Papers which mention “Hokkaido University” in the acknowledgements.
Journals in English published by Japanese publishers are listed as “International Journals”.
[JP] Japanese Publishers[OV] Overseas Publishers[Proc] International Conference Proceedings
Collaborative papers between HU and overseas GI-CoRE members are marked with “@GI-CoRE”.

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1. International Collaborative Papers: #64 in total
1-1. Featured in International Journals: #51
2021-2020
1)

Y. Jung, M. Wada, K. Shibahara, S. Jain, I. A. Davidson, P. Barua, J. R. Hayes, T. Sakamoto, T. Mizuno, Y.
Miyamoto, Y. Sasaki, K. Saitoh, K. Nakajima, and D. J. Richardson, “High Spatial Density 6-Mode 7-Core
Fiber Amplifier for L-Band Operation”, IEEE/OSA Journal of Lightwave Technology, vol. 38, no. 11, pp.
2938-2943, June 2020. [OV] †2)Naoki Osada, Kazunari Matsudaira, Yuzuru Hamada, Suchinda Malaivijitnond. Testing sex-biased
admixture origin of macaque species using autosomal and X-chromosomal genomic sequences. Genome
Biol. Evol. in press (2021) [OV] †3)

Yue Li, Kazumichi Fujiwara, Naoki Osada, Yosuke Kawai, Toyoyuki Takada, Alexey P. Kryukov, KuniyaAbe, Hiromichi Yonekawa, Toshihiko Shiroishi, Kazuo Moriwaki, Naruya Saitou, Hitoshi Suzuki. House
mouse Mus musculus dispersal in East Eurasia inferred from 98 newly determined complete mitochondrial
genome sequences. Heredity 126: 32–147(2021) [OV] †4)

Juliano Rabelo, Mi-Young Kim, Randy Goebel, Masaharu Yoshioka, Yoshinobu Kano, and Ken Satoh : A
Summary of the COLIEE 2019 Competition. In New Frontiers in Artificial Intelligence. JSAI-isAI 2019.
Lecture Notes in Computer Science, pp. 34-49, Springer International Publishing, Cham, LNCS12331,
2020. [OV]*i) †5)

Juliano Rabelo, Mi-Young Kim, Randy Goebel, Masaharu Yoshioka, Yoshinobu Kano and Ken Satoh:
COLIEE 2020: Methods for Legal Document Retrieval and Entailment. In Proceedings of the International
Workshop on Juris-Informatics 2020 (JURISIN 2020) in association with the 12th JSAI International
Symposia on AI (JSAI-isAI 2020), pp. 114-127, The Japanese Society of Artificial Intelligence, 2020.
[OV]*i) †6)

Jessica R. Deere, Summer Streets, Mark D. Jankowski, Mark Ferrey, Yvette Chenaux-Ibrahim, Matteo
Convertino, EJ Isaac, Nicholas B. D. Phelps, Alexander Primus, Joseph L. Servadio, Randall S. Singer,
Dominic A. Travis, Seth Moore, Tiffany M. Wolf, (2021), A chemical prioritization process: Applications
to contaminants of emerging concern in freshwater ecosystems (Phase I), Science of the Total
Environment, [OV] †7)

Servadio J, Deere J, Mark D. Jankowski, Mark Ferrey, EJ Isaac, Yvette Chenaux-Ibrahim, Alexander
Primus, Convertino M, Nicholas B. D. Phelps, Summer Streets, Dominic A. Travis, Seth Moore, Tiffany
M. Wolf, (2021), Anthropogenic factors associated with contaminants of emerging concern detected ininland Minnesota lakes (Phase II), Science of the Total Environment, in press [OV] †8)

Li J, Convertino M, (2021), Inferring Ecosystem Networks as Information Flows, Scientific Reports, inpress [OV] †9)

Li J, Convertino M, (2021), Temperature-driven Organization of Fish Ecosystems and Fishery Implications,71

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PLoS ONE, doi: https://doi.org/10.1101/2021.01.18.427097, PLoS ONE, in press [OV] †10) Louis Yat Hin Chan, Baoyin Yuan, Matteo Convertino, COVID-19 Communication and Systemic Portfolio
Risk, Sci. Report, in press [OV] †11) Convertino M, Honore Peggy, Victor J. Del Rio-Vilas, 2020, Portfolio Evaluation and Design ofSurveillance Systems, Ecological Indicators, in press [OV] †12) B. Pahlavsay, E. Palezzato and M. Torielli, Domination in latin square graphs. arXiv:1911.10673. To
appear in Graphs and Combinatorics.[OV] *i)13) E. Palezzato and M. Torielli, Combinatorially equivalent hyperplane arrangements. arXiv:1906.05463. To
appear in Advances in Applied Mathematics.[OV] *i)14) M. Torielli and S. Tsujie, Freeness of hyperplane arrangements between boolean arrangements and Weylarrangements of type Bl. The Electronic Journal of Combinatorics, 27(3), 2020.
https://doi.org/10.37236/9341.[OV]*i)
15) E. Palezzato and M. Torielli, Localization of plus-one generated arrangements. Communications in
Algebra, vol. 49(1), 301–309, 2021. https:// doi.org/ 10.1080/00927872.2020.1798976.[OV] *i)
16) W. Guo and M. Torielli, On the Falk invariant of Shi and Linial arrangements. Discrete & Computational
Geometry, 2020. https://doi.org/10.1007/s00454-020-00266-0. [OV] †17) Liu Y, Saha S, Hoppe B, Convertino M, “One Size Does Not Fit All: Tailoring Impacts of Ambient
Temperature on Children’s Health by Age”, Lancet Child & Adolescent Health, 2020, in press, [OV]*i)18) Cullen CM, Kawalpreet K Aneja, Sinem Beyhan, Clara E. Cho, Stephen Woloszynek, Matteo
Convertino, Sophie J. McCoy, Yanyan Zhang, Matthew Z. Anderson, David Alvarez-Ponce, Ekaterina
Smirnova, Lisa Karstens, Pieter C. Dorrestein, Hongzhe Li, Ananya Sen Gupta, Kevin Cheung, Jennifer
Gloeckner Powers, Zhengqiao Zhao, and Gail Rosen, “Emerging Priorities for Microbiome Research,
Frontiers in Microbiology”, 2020, [OV]*i)19) Deere J, Moore S, Ferrey M, Jankowski MD, Primus A, Convertino M, Servadio JL, Phelps NBD, Hamilton
MC, Chenaux-Ibrahim Y, Travis DA, Wolf TM, “Characterization of contaminants of emerging concern inaquatic ecosystems utilized by Minnesota tribal communities”, Science of the Total Environment, 2020,[OV]*i)20) Servadio JL, Muñoz-Zanzi C, Fiecas M, Convertino M, “Sensitivity to temporal resolution whencharacterizing Yellow Fever incidence”, Science Advances, 2020, in press [OV]*i)21) Servadio JL, Machado G, Alvarez J, de Ferreira Lima Júnior FE, Vieira Alves R, Convertino M,“Information differences across spatial resolutions and scales for disease surveillance: the case of Visceral
Leishmaniasis in Brazil”, Royal Society Open Science, 2020, [OV]*i)
201922) Hay Mar Soe Naing, Risanuri Hidayat, Bondhan Winduratna, Yoshikazu Miyanaga, “Psychoacoustical
Masking Effect-Based Feature Extraction for Robust Speech Recognition,” International Journal of
Innovative Computing, Information and Control, Vol. 15, No. 5, pp. 1641-1654, Oct. 2019.

72

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[doi:10.24507/ijicic.15.05.1641] [ISSN:1349-4198] [OV]*ii)23) Htoo Maung Maung, Supavadee Aramvith, Yoshikazu Miyanaga, “Hierarchical-P Reference Picture
Selection Based Error Resilient Video Coding Framework for High Efficiency Video Coding Transmission
Applications,” Electronics, Vol. 8, No. 3, Mar. 2019. [doi:10.3390/electronics8030310] [ISSN:2079-9292][OV]24) Ei Ei Tun, Supavadee Aramvith, Yoshikazu Miyanaga, “Fast Coding Unit Encoding Scheme for HEVC
Using

Genetic

Algorithm,”

IEEE

Access,

Vol.

7,

pp.

68010-68021,

Mar.

2019.

[doi:10.1109/ACCESS.2019.2918508] [ISSN:2169-3536] [OV]25) R. S. Luis, G. Rademacher, B. J. Puttnam, T. A. Eriksson, H. Furukawa, A. Ross-Adams, S. Gross, M.
Withford, N. Riesen, Y. Sasaki, K. Saitoh, K. Aikawa, Y. Awaji, N. Wada, “1.2 Pb/s Throughput
transmission using a 160 micrometer cladding, 4-core, 3-mode fiber”, IEEE/OSA Journal of Lightwave
Technology, vol. 37, no. 8, pp. 1798-1804, Apr. 2019. [OV]
26) Gabriel Gonzalez, Camden R. Bair, Daryl M. Lamson, Hidemi Watanabe, Laura Panto, Michael J. Carr,
Adriana E. Kajon, “Genomic characterization of human adenovirus type 4 strains isolated worldwide since1953 identifies two separable phylogroups evolving at different rates from their most recent common
ancestor”, Virology, 538:11-23, 2019 [OV] *i)27) Alfarozi, S., Pasupa, K., Woraratpanya, K., Sugimoto, M.: Local Sigmoid Method: Non-iterative
Deterministic Learning Algorithm for Automatic Model Construction of Neural Network, IEEE Access,Vol. 8, 2019 [OV]28) Alfarozi, S., Pasupa, K., Hashizume, H., Woraratpanya, K., Sugimoto, M.: Robust and Unified VLC
Decoding System for Square Wave Quadrature Amplitude Modulation Using Deep Learning Approach,IEEE Access, Vol. 7, pp. 163262-163276, 2019. [OV]*ii)
29) Alfarozi, S., Hashizume, H., Pasupa, K., Woraratpanya, K., Sugimoto, M.: Square Wave Quadrature
Amplitude Modulation for Visible Light Communication using Image Sensor, IEEE Access, Vol. 7,
pp.94806-94821, 2019. [OV]*ii)
30) Asano Ishikawa, Naoki Kabeya, Koki Ikeya, Ryo Kakioka, Jennifer N. Cech, Naoki Osada, Miguel C. Leal,
Jun Inoue, Manabu Kume, Atsushi Toyoda, Ayumi Tezuka, Atsushi J. Nagano, Yo Y. Yamasaki, Yuto Suzuki,
Tomoyuki Kokita, Hiroshi Takahashi, Kay Lucek, David Marques, Yusuke Takehana, Kiyoshi Naruse,
Seiichi Mori, Oscar Monroig, Nemiah Ladd, Carsten J. Schubert, Blake Matthews, Catherine L. Peichel,
Ole Seehausen, Goro Yoshizaki, Jun Kitano. “Key metabolic gene for recurrent freshwater colonization
and radiation in fishes”, Science, 364: 886-889 (2019). [OV]
31) Yukiko Nakamura, Junya Yamagishi, Kyoko Hayashida, Naoki Osada, Elisha Chatanga, Cornelius
Mweempwa, Kalinga Chilongo, John Chisi, Jenelisa Musaya, Ryosuke Omori, Noboru Inoue, Boniface
Namangala, Chihiro Sugimoto. “Genetic diversity and population structure of Glossina morsitans
morsitans in the active foci of human African trypanosomiasis in Zambia and Malawi”. PLoS Negl. Trop.
Dis. 13: e0007568 (2019). [OV] *i)32) Johansson M et al. (CDC Forecasting Challenge Team) … Convertino M, “Advancing probabilistic
epidemic forecasting through an open challenge: The Dengue Forecasting Project”, PNAS, 2019 [OV]*ii)

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33) Convertino M and Valverde JL, “Toward a Pluralistic Conception of Resilience, Ecological Indicators,
2019, [OV]*i) ii)
34) Y Liu, S Saha, BO Hoppe, M Convertino, “Degrees and dollars–Health costs associated with suboptimal
ambient temperature exposure”, 2019, Science of The Total Environment [OV]*i)35) Valverde LJ, M Convertino, “Insurer Resilience in an Era of Climate Change and Extreme Weather: An
Econometric Analysis”, 2019, Climate 7 (4), 55 [OV]36) M Convertino, A Annis, F Nardi, “Information-theoretic Portfolio Decision Model for Optimal FloodManagement”, 2019, Env Mod and Software [OV]*i) ii)
37) McGowan et al. (CDC Forecasting Challenge Team) … Convertino M, “Collaborative efforts to forecast
seasonal influenza in the United States (2015–2016)”, 2019, Scientific Reports [OV]*i)38) Convertino M, Valverde J Jr., “Metacommunity Resilience of the Amazon Tropical Forest Facing Humanand Natural Stressors”, Ecological Modeling, 2019, in review [OV]*Not accepted and excluded from the final counts.
39) Reddy A, Liu Y, Munoz-Zanzi C, Convertino M, “Neutral Early Warning Model, Criticality, and Ecoepidemiological Scaling for Infectious Diseases”, 2019, Environmental Modeling and Software, in review[OV]*Accepted as “Eco-epidemiological scaling of Leptospirosis: Vulnerability mapping and early warning
forecasts” as of 13 July 2021.
40) Marc Härkönen, Tomonari Sei, Yoshihiro Hirose. “Holonomic Extended Least Angle Regression”,
Information Geometry. accepted, [2019] [OV]41) David Avis, Charles Jordan, “mts: a light framework for parallelizing tree search codes”, Optimization
Methods and Software, DOI: 10.1080/10556788.2019.1692344, 2019 [OV]201842) M. Nooruzzaman, K. Saitoh, Y. Sasaki, K. Takenaga, K. Aikawa, and T. Morioka, “Non-circular multi-core
fibers for super-dense SDM”, IEICE Electronics Express, vol. 15, no. 19, pp. 1-12, Sep. 2018. [JP]43) Fan, Zhenxin, Anbo Zhou, Naoki Osada, Jianqiu Yu, Juan Jiang, Peng Li, Lianming Du, Lili Niu, Jiabo
Deng, Huailiang Xu, Jinchuan Xing, Bisong Yue, Jing Li. “Ancient hybridization and admixture in
macaques (genus Macaca) inferred from whole genome sequences.” Mol. Phyl. Evol. 127: 376-386 (2018).
[OV]44) Convertino M, Honore P, Del Rio-Vilas V, “An Information-theoretic Portfolio Model for Disease
Surveillance Design”, September 2018, DOI:10.13140/RG.2.2.16620.82560, Risk Analysis [OV]45) Servadio J et al… Convertino M, “Demographic Inequities in Health Outcomes and Air Pollution Exposurein the Atlanta Area and its Relationship to Urban Infrastructure”, October 2018, Journal of Urban Health[OV]46) Servadio J, Convertino M, “Optimal information networks: Application for data- driven integrated healthin populations”, 2018, Science Advances [OV] *i) ii)
47) Convertino M et al., “Stochastic Pharmacokinetic Pharmacodynamic Modeling for Assessing the Systemic
Health Risk of Perfluorooctanoate (PFOA)”, 2018, Toxicological Sciences [OV] *ii)

74

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2021/11/12 9:4448) Liu Y, Hoppe BO, Convertino M, “Threshold Evaluation of Emergency Risk Communication for Health
Risks Related to Hazardous Ambient Temperature”, 2018, Risk Analysis [OV] *i)49) Charles Jordan, Michael Joswig, Lars Kastner. “Parallel Enumeration of Triangulations”, Electronic
Journal of Combinatorics 25(3), #P3.6, 2018 [OV]50) A.M. Bigatti, E. Palezzato and M. Torielli, “New characterizations of freeness for hyperplanearrangements.” Journal of Algebraic Combinatorics, 2018.

https://doi.org/10.1007/s10801-019-00876- 9.

[OV]
2017
51) X. Xie, J. Tu, X. Zhou, K. Long, and K. Saitoh, “Design and optimization of 32-core rod/trench assisted
square-lattice structured single-mode multi-core fiber”, Optics Express, vol. 25, no. 5, pp. 5119-5132, Mar.
2017. [OV]52) T. Mizuno, K. Shibahara, F. Ye, Y. Sasaki, Y. Amma, K. Takenaga, Y. Jung, K. Pulverer, H. Ono, Y. Abe,M. Yamada, K. Saitoh, S. Matsuo, K. Aikawa, M. Bohn, D. J. Richardson, Y. Miyamoto, and T. Morioka,“Long-haul dense space division multiplexed transmission over low-crosstalk heterogeneous 32-coretransmission line using partial recirculating loop system”, IEEE/OSA Journal of Lightwave Technology,
vol. 35, no. 3, pp. 488-498, Feb. 2017. [OV]53) David Avis, Charles Jordan, “mplrs: A scalable parallel vertex/facet enumeration code”, Mathematical
Programming Computation, 2017 [OV]1-2. Featured in International Conference Proceedings: #13
2021-20201)

Keshavarz Rasool, Miyanaga Yoshikazu, Yamamoto Manabu, Hikage Takashi, Shariati Negin:"Metamaterial-Inspired Quad-Band Notch Filter for LTE Band Receivers and WPT Applications(Invited),"proc. of XXXIV General Assembly and Scientific Symposium (GASS) of the International Union of Radio
Science (Union Radio Scientifique Internationale-URSI), DK01-01, Aug. 2020. [Proc] *i) † @GI-CoRE
2019

2)

Hay Mar Soe Naing, Yoshikazu Miyanaga, Risanuri Hidayat, Bondhan Winduratna, “Filterbank Analysisof MFCC Feature Extraction in Robust Children Speech Recognition,” Proceedings of International
Symposium on Multimedia and Communication Technology (ISMAC), Aug. 2019. [OV][Proc]*i)3)Sovann Chen, Supavadee Aramvith, Yoshikazu Miyanaga, “Encoder Control Enhancement in HEVC
Based on R-Lambda Coefficient Distribution,” Proceedings of International Symposium on Multimedia
and Communication Technology (ISMAC), Aug. 2019. [OV] [Proc]

4)

Ei Ei Tun, Supavadee Aramvith, Yoshikazu Miyanaga, “A Fast CU Depth Estimation Algorithm for HEVC
Inter Coding,” Proceedings of 2019 IEEE International Conference on Consumer Electronics - Asia (ICCEAsia), Jun. 2019. [OV][Proc]

5)

Yoshinobu Kan, Mi-Young Kim, Masaharu Yoshioka, Yao Lu, Juliano Rabelo, Naoki Kiyota, Randy
Goebel, and Ken Satoh: COLIEE-2018: Evaluation of the Competition on Legal Information Extraction
and Entailment. In New Frontiers in Artificial Intelligence. JSAI-isAI 2018. Lecture Notes in Computer

75

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Science, pp. 177-192, Springer International Publishing, Cham, LNCS11717, 2019. [OV] [Proc] *i)
6)Juliano Rabelo, Mi-Young Kim, Randy Goebel, Masaharu Yoshioka, Yoshinobu Kano and Ken Satoh:
COLIEE 2019 Overview. In Proceedigns of the Sixth International Competition on Legal Information
Extraction/Entailment (COLIEE 2019), pp. 1-9, 2019. [OV] [Proc]*i)7)

Yuko Sakurai, Satoshi Oyama, Mingyu Guo, and Makoto Yokoo, “Deep false-name-proof auction
mechanisms”, Proceedings of the 22nd International Conference on Principles and Practice of Multi-Agent
Systems (PRIMA 2019), pp. 594-601, 2019. [OV] [Proc]
2018

8)

Ei Ei Tun, Supavadee Aramvith, Yoshikazu Miyanaga, “Feature Reduction on Fuzzy SVM-Based Coding
Unit Decision in HEVC,” Proceedings of International Conference on Engineering, Applied Sciences andTechnology (ICEAST 2018), pp. 999-1002, Track 4 (Telecommunications, Computer Science,
Instrumentation and Control, Electrical and Electronic Engineering), Jul. 2018. [OV] [Proc]

9)

Hay Mar Soe Naing, Risanuri Hidayat, Bondhan Winduratna, Yoshikazu Miyanaga, “Comparison of Three
Auditory Frequency Scales in Feature Extraction on Myanmar Digits Recognition,” Proceedings ofInternational Conference on Information Technology and Electrical Engineering (ICITEE), pp. 254-259,
Jul. 2018. [OV][Proc]

10) Masaharu Yoshioka, Myungha Jang, James Allan, and Noriko Kando: Visualizing Polarity-based Stancesof News Websites. In Proceedings of the Second International Workshop on Recent Trends in News
Information Retrieval co-located with 40th European Conference on Information Retrieval (ECIR 2018)
Grenoble, France, March 26, 2018, pp. 6-8, 2018 [OV]@GI-CoRE11) Kei Takada, Hiroyuki Iizuka, Subhransu Maji, Masahito Yamamoto, “Mutual learning between human andmachine to develop a human-machine interface to operate multi-DOF robots”, 24th International
Symposium on Artificial Life and Robotics (AROB 24th 2019), 2019, [JP, International Conference] [Proc]*ii)@GI-CoRE
12) Kyohei Atarashi, Subhransu Maji, and Satoshi Oyama, “Random Feature Maps for the Itemset Kernel”, In
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), pp. 3199-3206,
January 2019. [OV] [Proc] *ii) @GI-CoRE
13) A.M. Bigatti, E. Palezzato and M. Torielli, “Two new characterizations of free hyperplane arrangements.”
Monografias de la Real Academia de Ciencias. Zaragoza. 43: 59-62, (2018). ISSN: 1132-6360. [OV][Proc]

2. Other Publications: #471 in total
2-1. Featured in International Journals: #176
2021-2020
1)

M. Shirata, T. Fujisawa, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh, “Design of small modedependent-loss scrambling-type mode (de)multiplexer based on PLC”, Optics Express, vol. 28, no. 7, pp.
9653-9665, Mar. 2020. †2)

T. Sakamoto, K. Saitoh, S. Saitoh, Y. Abe, K. Takenaga, A. Urushibara, M. Wada, T. Matsui, K. Aikawa,76

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and K. Nakajima, “Spatial Density and Splicing Characteristic Optimized Few-Mode Multi-Core Fiber”,
IEEE/OSA Journal of Lightwave Technology, vol. 38, no. 16, pp. 4490-4496, Aug. 2020. †3)

T. Fujisawa and K. Saitoh, “Geometric-phase-induced arbitrary polarization and orbital angular momentum
generation in helically twisted birefringent photonic crystal fiber”, Photonics Journal, vol. 8, no. 8, pp.
1278-1288, Aug. 2020. †4)

Y. Sawada, T. Fujisawa, and K. Saitoh, “Broadband and compact silicon mode converter designed using a
wavefront matching method”, Optics Express, vol. 28, no. 25, pp. 38196-38205, Dec. 2020. †5)

T. Fujisawa, J. Takano, Y. Sawada, and K. Saitoh, “Low-loss and small 2×4λ multiplexers based on 2×2
and 2×1 Mach-Zehnder interferometers with on-chip polarization multiplexing for 400GbE”, IEEE/OSA
Journal of Lightwave Technology, vol. 39, no. 1, pp. 193-200, Jan. 2021. †6)

Keisuke Maeda, Kazaha Horii, Takahiro Ogawa, Miki Haseyama: "Multi-task convolutional neuralnetwork leading to high performance and interpretability via attribute estimation", IEICE
TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences,
vol.Vol.E103-A, no.12, pp.1609-1612 (2020) †7)

Soh Yoshida, Mitsuji Muneyasu, Takahiro Ogawa, Miki Haseyama: "Heterogeneous-Graph-Based video
search reranking using topic relevance", IEICE TRANSACTIONS on Fundamentals of Electronics,
Communications and Computer Sciences, vol.Vol.E103-A, no.12, pp.1529-1540 (2020) †8)

Takahiro Ogawa, Keisuke Maeda, Miki Haseyama: "Inpainting via sparse representation based on aphaseless quality metric", IEICE TRANSACTIONS on Fundamentals of Electronics, Communications andComputer Sciences, vol.Vol.E103-A, no.12, pp.1541-1551 (2020) †9)

Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: "Deterioration level estimation via
neural network maximizing category-based ordinally supervised multi-view canonical correlation",
Multimedia Tools and Applications, pp.1-12 (2020) †10) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Human-centric emotion estimation
based on correlation maximization considering changes with time in visual attention and brain activity",IEEE Access, vol.8, pp.203358-203368 (2020) †11) Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: "Brain Decoding of Viewed
Image Categories via Semi-supervised Multi-view Bayesian Generative Model", IEEE Transactions on
Signal Processing, vol.68, pp.5769-5781 (2020) †12) Ren Togo, Haruna Watanabe, Takahiro Ogawa, Miki Haseyama: "Deep convolutional neural networkbased anomaly detection for organ classification in gastric X-ray examination", Computers in Biology andMedicine, vol.123, pp.103903 (2020) †13) Keisuke Maeda, Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: "Estimation ofinterest levels from behavior features via tensor completion including adaptive similar user selection",

77

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IEEE Access, vol.8, pp.126109-126118 (2020) †14) Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Chronic atrophic gastritis detection with aconvolutional neural network considering stomach regions", World Journal of Gastroenterology, vol.26,
no.25, pp.3650-3659 (2020) †15) Keisuke Maeda, Susumu Genma, Takahiro Ogawa, Miki Haseyama: "Image retrieval based on supervised
local regression and global alignment with relevance feedback for insect identification", ITE Transactions
on Media Technology and Applications, vol.8, no.3, pp.140-150 (2020) †16) Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: "A method for player importanceprediction from player network using gaze position estimated by LSTM", ITE Transactions on Media
Technology and Applications, vol.8, no.3, pp.151-160 (2020) †17) Keisuke Maeda, Yoshiki Ito, Takahiro Ogawa, Miki Haseyama: "Supervised fractional-order embedding
geometrical multi-view CCA (SFGMCCA) for multiple feature integration", IEEE Access, vol.8,
pp.114340–114353 (2020) †18) Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Enhancing cross-modal retrieval based onmodality-specific and embedding spaces", IEEE Access, vol.8, pp.96777-96786 (2020) †19) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Few-shot personalized saliency
prediction based on adaptive image selection considering object and visual attention", Sensors, vol.20,
no.8: 2170, pp.1-15 (2020) †20) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Tensor-based emotional categoryclassification via visual attention-based heterogeneous CNN feature fusion", Sensors, vol.20, no.7: 2146,
pp.1-15 (2020) †21) Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: "Multimodal important scene
detection in far-view soccer videos based on single deep neural architecture", ITE Transactions on Media
Technology and Applications, vol.8, no.2, pp.89-99 (2020) †22) Kazaha Horii, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Interpretable convolutional neuralnetwork including attribute estimation for image classification", ITE Transactions on Media Technology
and Applications, vol.8, no.2, pp.111-124 (2020) †23) Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Detection of Important Scenes in
Baseball Videos via a Time-Lag-Aware Multimodal Variational Autoencoder ", Sensors, vol.21, no.6:
2045, pp.1-11 (2021) †24) Ren Togo, Naoki Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: " Rubber material property
prediction using electron microscope images of internal structures taken under multiple conditions",
Sensors, vol.21, no.6: 2088, pp.1-13 (2021) †25) Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: "Perceived image decoding
from brain activity using shared information of multi-subject fMRI data", IEEE Access, vol.9, pp.26593–

78

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26606 (2021) †26) Masanao Matsumoto, Naoki Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Supervised
fractional-order embedding Multiview canonical correlation analysis via ordinal label dequantization forimage interest estimation", IEEE Access, vol.9, pp.21810–21822 (2021) †27) Yuya KASE, Toshihiko NISHIMURA, Takeo OHGANE, Yasutaka OGAWA, Daisuke KITAYAMA andYoshihisa KISHIYAMA: Fundamental Trial on DOA Estimation with Deep Learning, IEICE
TRANSACTIONS on Communications, VOL.E103-B NO.10 OCTOBER 2020, p1127-1135 †28) Yuta Takano, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, and Junichiro Hagiwara: Channel
prediction of wideband OFDM systems in a millimeter-wave band based on multipath delay estimation,
IEICE Communications Express, Vol.9, No.12, 561–566, DOI: 10.1587/comex.2020COL0002 Received
April 8, 2020 Accepted April 23, 2020 Publicized May 14, 2020 †29) Toshihiko NISHIMURA, Yasutaka OGAWA, Takeo OHGANE, Junichiro HAGIWARA, “RadioTechniques Incorporating Sparse Modeling”, IEICE TRANSACTIONS on Fundamentals of Electronics,
Communications and Computer Sciences, Vol.E104-A, No.3, pp.591-603, Mar. 2021 †30) Murakami, H., Nakamura, M., Hashizume, H., Sugimoto, M.: Five Degrees-of-freedom Pose-estimation
Method for Smartphones using a Single Acoustic Anchor, IEEE Sensors Journal (to appear in 2021).*ii) †31) Masaki Kawamoto, Toshiyuki Yamaji, Kyoko Saito, Yoshitaka Shirasago, Kazuhiro Satomura, ToshinoriEndo, Masayoshi Fukasawa, Kentaro Hanada, Naoki Osada. Identification of characteristic genomic
markers in human epatoma HuH-7 and Huh7.5.1-8 Cell Lines. Frontiers in Genetics

11: 546106 (2020)†32) Kyoko Saito, Masayoshi Fukasawa, Yoshitaka Shirasago, Ryosuke Suzuki, Naoki Osada, Toshiyuki Yamaji,
Takaji Wakita, Eiji Konishi, Kentaro Hanada. Comparative characterization of flavivirus production in twocell lines: Human hepatoma-derived Huh7.5.1-8 and African green monkey kidney-derived Vero. PLOSONE

15: e0232274 (2020) †33) Naoki Osada*, Yosuke Kawai. Exploring models of human migration to the Japanese archipelago using
genome-wide genetic data. Anthropol. Sci. in press (2021). †34) Convertino M, 2020, Japan’s pandemic response: there is no one-size-fits-all approach to COVID-19,
Policy Forum, Asia and the Pacific Policy Society, https://www.policyforum.net/japans-pandemicresponse/?fbclid=IwAR0ALcdMHa8ZkewJsVLZwysV2TEFdEAOiNNBONO8iog1ea_O 724bcprb-BM†35) Kyohei Atarashi, Satoshi Oyama, and Masahito Kurihara: Link Prediction Using Higher-Order Feature
Combinations across Objects, IEICE Transactions on Information and Systems, Vol. E103-D, No. 8, pp.
1833-1842, August 2020. [OV] *ii) †36) Myat Hsu Aung, Hiroshi Tsutsui, Yoshikazu Miyanaga, "WiFi Fingerprint Based Indoor Positioning
Systems Using Estimated Reference Locations," IEICE Transactions on Fundamentals of Electronics,
Communications and Computer Sciences, Vol. E103-A, No. 12, pp. 1483-1493, Dec. 2020.

79

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[doi:10.1587/transfun.E103.A.1483][OV] *ii) †37) Takashi Hikage, Suzune Ito, and Atsuki Ohtsuka: "Novel Interference Voltage Measurement for BeamType Wireless Power Transfer Using an Electro-Optical Converter for EMI Assessment of Active
Implantable Medical Devices," URSI RADIO SCIENCE LETTERS, VOL. 2, pp.1-3, Nov. 2020. DOI:
10.46620/20-0039 [OV] †38) Toru Ishihara, Keiko Yamazaki, Atsuko Araki, Yuri Teraoka, Naomi Tamura, Takashi Hikage, Manabu
Omiya, Masahiro Mizuta, Reiko Kishi: "Exposure to Radiofrequency Electromagnetic Field in the HighFrequency Band and Cognitive Function in Children and Adolescents: A Literature Review," International
Journal of Environmental Research and Public Health, 17(24), 9179, Dec. 2020. [OV] †39) F. Kazemnejad, B. Pahlavsay, E. Palezzato and M. Torielli, Domination number of middle graphs.
arXiv:2008.02975. [OV] *i) †40) H. Imai, “Shift Invariance property of a non-negative matrix factorization”, IEICE transactions on
Fundamentals, Vol. E103-A, NO. 2, 2020 [JP] *i)41) Jing Song, Satoshi Oyama, and Masahito Kurihara, “Exploratory causal analysis of open data: explanation
generation and confounder identification”, Journal of Advanced Computational Intelligence and Intelligent
Informatics (JACIII), Vol. 24, No. 1, pp. 142-155, 2020. [JP]201942) Li J, Convertino M, 2020, “Taming Network Inference: Optimal Information Flow Model”, Sci. Adv.,
submitted [OV] *i)*Accepted as “Inferring ecosystem networks as information flows” as of 8 March 2021.
43) Chan L, Convertino M, 2020, “Systemic Risk Portrayal: the Contagion Epitome”, Risk Analysis, submitted[OV] *i)*Not accepted and excluded from the final counts.
44) Convertino M, 2020, “Detecting Multi-source Outbreak Pathways: Disentangling Local and Global Driversof Foodborne Infections”, BMC Public Health, submitted [OV]*Not accepted and excluded from the final counts.
45) Dabwitso Kasauka, Kenta Sugiyama, Hiroshi Tsutsui, Hiroyuki Okuhata, Yoshikazu Miyanaga,”An
Architecture for Real-Time Retinex-Based Image Enhancement and Haze Removal and Its FPGA
Implementation,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer
Sciences, Vol. E102-A, No. 6, pp. 775-782, Jun. 2019. [doi:10.1587/transfun.E102.A.775] [JP]*i)ii)
46) Yoichi Sasaki, Tetsuo Shibuya, Kimihito Ito and Hiroki Arimura, “Efficient Approximate 3-Dimensional
Point Set Matching Using Root-Mean-Square Deviation Score”, IEICE Trans. fundamentals, Vol.E102-A,
No.9, Sep. 2019. [JP](An extended abstract is appeared in: Proc. 8th International Conference on
Similarity Search and Applications (SISAP 2015), Lecture Notes in Computer Science 9371, Springer,
pp.191-203, 2015 (12-14 October 2015, Glasgow, Scotland, UK))47) Takuya Takagi, Shunsuke Inenaga, Hiroki Arimura, Dany Breslauer, and Diptarama Hendrian, “FullyOnline Suffix Tree and Directed Acyclic Word Graph Construction for Multiple Texts”, Algorithmica, 2019.

80

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(Also available as: arXiv:1507.07622) [OV]Note: In memory of Dr. Dany Breslauer: The above paper isthe revised version of the earlier paper presented in CPM2016, Tel Aviv, where the fully-only maintenancemechanism for suffix tree labels is improved by the joint work with Dr. Dany Breslauer, and later Dr.
Diptarama Hendrian.
48) Hiroya Inakoshi, Junichi Shigezumi, Tatsuya Asai, Takuya Kida, Hiroki Arimura, “Route graph: joint mapmatching by maximizing posterior probability”, IPSJ Transactions on Mathematical Modeling and Its
Applications, IPSJ, Vol.12, No.1, 19, Mar. 2019. [JP]49) Kunihiro Wasa, Katsuhisa Yamanaka, Hiroki Arimura, “The Complexity of Induced Tree Reconfiguration
Problems”, IEICE Trans. Inf. and Syst., Vol.102-D, No.3, 464-469, March 2019. DOI:
doi:10.1587/transinf.2018FCP0010, (Also appeared in LATA 2016) [JP]50) S. Nakano, T. Fujisawa, and K. Saitoh, “The effect of core offset on the mode converting characteristics intwisted single mode fibers”, IEEE/OSA Journal of Lightwave Technology, vol. 37, no. 21, pp. 5479-5485,
Nov. 2019. [OV]51) T. Fujisawa, J. Takano, Y. Sawada, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh, “A novel Si fourwavelength multiplexer for 100/400GbE using higher-order mode composed of (a)symmetric directional
couplers and TE1-TM0 mode converter”, Optics Express, vol. 27, no. 25, pp. 36286-36296, Dec. 2019.
[OV]52) T. Fujisawa, J. Takano, Y. Sawada, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh, “A novel Si fourwavelength multiplexer for 100/400GbE using higher-order mode composed of (a)symmetric directional
couplers and TE1-TM0 mode converter”, Optics Express, vol. 27, no. 25, pp. 36286-36296, Dec. 2019.
[OV]53) S. Nakano, T. Fujisawa, and K. Saitoh, “The effect of core offset on the mode converting characteristics intwisted single mode fibers”, IEEE/OSA Journal of Lightwave Technology, vol. 37, no. 21, pp. 5479-5485,
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[OV]55) K. Yoshida, T. Fujisawa, T. Sato, and K. Saitoh, “Optimum index profile of few-mode coupled multicore
fibers for reducing the group delay spread”, Optics Express, vol. 27, no. 11, pp. 16281-16295, May 2019.
[OV]56) T. Fujisawa, M. Arai, and K. Saitoh, “Microscopic gain analysis of modulation-doped GeSn/SiGeSnquantum wells: Epitaxial design toward high-temperature lasing”, Optics Express, vol. 27, no. 3, pp. 24572464, Feb. 2019. [OV]57) M. Kudo, S. Ohta, E. Taguchi, T. Fujisawa, T. Sakamoto, T. Matsui, K. Tsujikawa, K. Nakajima, and K.
Saitoh, “Proposal of Mach-Zehnder Mode/Wavelength Multi/Demultiplexer based on Si/Silica Hybrid PLC
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Feb. 2019. [OV]59) Y. Sawada, T. Fujisawa, T. Sato, and K. Saitoh, “CMOS-compatible Si-wire Polarization Beam Splitter
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[JP]60) K. Shibahara, T. Mizuno, D. Lee, Y. Miyamoto, H. Ono, K. Nakajima, Y. Amma, K. Takenaga, and K.
Saitoh, “Iterative Unreplicated Parallel Interference Canceler for MDL-Tolerant Dense SDM (12-Core ×
3-Mode) Transmission over 3000 km”, IEEE/OSA Journal of Lightwave Technology, vo. 37, no. 6, pp.
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Saitoh, “DMD-Unmanaged Long-Haul SDM Transmission Over 2500-km 12-Core × 3-Mode MC-FMF
and 6300-km 3-Mode FMF Employing Intermodal Interference Cancelling Technique”, IEEE/OSA Journalof Lightwave Technology, vol. 37, no. 1, pp. 138-147, Jan. 2019. [OV]62) Takahiro Ogawa, Kento Sugata, Ren Togo, Miki Haseyama: “Multi-classifier Decision: Integration ofMultiple Brain Activity-based Classifications”, ITE Transactions on Media Technology and Applications,vol.7, no.1, pp.36-44 (2019) [JP]63) Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama, “Text-to-image GAN-based scene retrieval
and re-ranking considering word importance” IEEE Access, vol.7, pp.169920-169930(2019) [OV]64) Ren Togo, Naoki Saito, Takahiro Ogawa, Miki Haseyama, “Estimating regions of deterioration in electron
microscope images of rubber materials via a transfer learning-based anomaly detection model”, IEEE
Access, vol.7, pp.162395-162404(2019) [OV]65) Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama, “Query is GAN: scene retrieval withattentional text-to-image generative adversarial network, “IEEE Access, vol.7, pp.153183-153193(2019)[OV]66) Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama, “Interest level estimation based on
tensor completion via feature integration for partially paired user's behavior and videos” IEEE Access,vol.7, no.1, pp.148576-148585(2019) [OV]67) Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama, “Team tactics estimation in soccer videos
based on a deep extreme learning machine and characteristics of the tactics” IEEE Access, vol.7,
pp.153238-153248(2019) [OV]68) Ryosuke Harakawa, Shoji Takimura, Takahiro Ogawa, Miki Haseyama, Masahiro Iwahashi, “Consensus
clustering of tweet networks via semantic and sentiment similarity estimation” IEEE Access, vol.7,
pp.116207-116217(2019) [OV]69) Yui Matsumoto, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama, “Music Video Recommendation
Based on Link Prediction Considering Local and Global Structures of a Network”, IEEE Access, vol.7,
no.1, pp.104155-104167(2019) [OV]70) Ren Togo, Takahiro Ogawa, Miki Haseyama, “Synthetic gastritis image generation via loss function-based
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Naoya Sakamoto, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama, “Detection of gastritis by a deep
convolutional neural network from double-contrast upper gastrointestinal barium X-ray radiography”,
Journal of Gastroenterology, vol.54, no.4, pp.321-329(2019) [OV] *ii)74) Ren Togo, Kenji Hirata, Osamu Manabe, Hiroshi Ohira Ichizo Tsujino, Keiichi Magota, Takahiro Ogawa,Miki Haseyama, Tohru Shiga: “Cardiac sarcoidosis classification with deep convolutional neuralnetworkbased features using polar maps”, Computers in Biology and Medicine, vol.104, pp.81-86 (2019)[OV] *ii)75) Kazaha Horii, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Human-centered image classification
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Shimizu, Miki Ueno, Toshimitsu Ito, Takashi Tamura, Mariko Naito, Hiroshi Nakashima, Makoto
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Communications and Computer Sciences, vol. E101-A, no.6, pp.900-903 (2018) [JP]105) Soh Yoshida, Takahiro Ogawa, Miki Haseyama, Mitsuji Muneyasu: “Graph-Based Video Search Reranking
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Locality Preserving Canonical Correlation Analysis”, IEICE Transactions on Information and Systems, vol.
E100-D, no.9, pp.2005-2016 (2017) [JP]147) Miki Haseyama, Takahiro Ogawa, Sho Takahashi, Shuhei Nomura, Masatsugu Shimomura: “Biomimetics
Image Retrieval Platform”, IEICE Transactions on Information and Systems, vol. E100-D, no.8, pp.15631573 (2017) [JP]148) Sho Takahashi, Miki Haseyama: “A Method of Important Player Extraction Based on Link Analysis in
Soccer Videos”, ITE Transactions on Media Technology and Applications, vol.5, no.2, pp.42-48 (2017)[JP]149) Takahiro Ogawa, Yoshiaki Yamaguchi, Satoshi Asamizu, Miki Haseyama: “Human-Centered Video
Feature Selection via mRMR-SCMMCCA for Preference Extraction”, IEICE Transactions on Informationand Systems, vol. E100-D, no.2, pp.409-412 (2017) [JP]150) Shota Hamano, Takahiro Ogawa, Miki Haseyama: “A Language-Independent Ontology Construction
Method Using Tagged Images in Folksonomy”, IEEE Access, vol.6, pp.2930-2942 (2017) [OV]151) Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Extracting Hierarchical Structure of Web Video
Groups Based on Sentiment-Aware Signed Network Analysis”, IEEE Access, vol.5, pp.16963-16973(2017) [OV]152) Daichi Takehara, Ryosuke Harakawa, Takahiro Ogawa, and Miki Haseyama: “Extracting Hierarchical
Structure of Content Groups From Different Social Media Platforms Using Multiple Social Metadata”,
Multimedia Tools and Applications, vol.76, no.19, pp.20249-20272 (2017) [OV]153) Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Helicobacter Pylori Infection Detection from Gastric
X-ray Images Based on Feature Fusion and Decision Fusion”, Computers in Biology and Medicine, vol.84,
no.1, pp.69-78 (2017) [OV]154) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Distress Classification of Road
Structures via Adaptive Bayesian Network Model Selection”, ASCE Journal of Computing in Civil
Engineering, vol.31, no.5, pp.04017044-1 - 04017044-13 (2017) [OV]155) Naoki Osada, Ryutaro Miyagi, Aya Takahashi. “Cis- and trans-regulatory effects on gene expression in anatural population of Drosophila melanogaster.” Genetics 206: 2139-2148 (2017). [OV]156) Yasuaki Takada, Ryutaro Miyagi, Toshinori Endo, Aya Takahashi, Naoki Osada. “A generalized linear
model for decomposing genetic, parent-of-origin, and maternal effects on allele-specific gene expression.”G3 7: 2227-2234 (2017). [OV]157) Convertino M, “Information Fractal Dimension as Communication Network Stability, IEICE technicalreport, 117 (349), 15-20, 2017 [JP]158) Junki Tanaka and Toru Ohmoto, “GEOMETRIC ALGEBRA AND SINGULARITIES OF RULED AND
DEVELOPABLE SURFACES”, accepted for publication in Journal of Singularities, special volume forthe proceedings of the conference “Geometric and Algebraic Singularity Theory”, held in Bedlewo during89

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September 10-16, 2017. [OV]*i)159) Yuji Takenobu, Norihito Yasuda, Shunsuke Kawano, Yasuhiro Hayashi, and Shin-ichi Minato: “Evaluationof Annual Energy Loss Reduction Based on Reconfiguration Scheduling,” IEEE Trans. Smart Grid, DOI
10.1109/TSG.2016.2604922, 2017 [OV]160) Reona Minoda, Shin-ichi Minato, “Verifying Scenarios of Proximity-Based Federations among Smart
Objects through Model Checking and Its Advantages”, IEICE Transactions on Information and Systems,
Vol. E100-D, No. 6, pp. 1172-1181, June 2017 [JP]161) Jun Kawahara, Takeru Inoue, Hiroaki Iwashita, Shin-ichi Minato, “Frontier-based Search for Enumerating
All Constrained Subgraphs with Compressed Representation”, IEICE Trans. Fundamentals, Vol. E100-A,
No. 9, pp. 1773-1784, Sep. 2017 [JP]162) Fumito Takeuchi, Masaaki Nishino, Norihito Yasuda, Takuya Akiba, Shin-ichi Minato, Masaaki Nagata,“BDD-Constrained A* Search: A Fast Method for Solving Constrained Shortest-Path Problems”, IEICE
Transactions on Information and Systems, Vol. E100-D, No. 12, pp. 2945-2952, Dec. 2017 [JP]163) Reona MINODA and Shin-ichi MINATO: “Verifying Scenarios of Proximity-based Federations among
Smart Objects through Model Checking and Its Advantages,” IEICE Trans. Inf. & Syst., 2017. [JP]2016164) Iku Ohama, Hiromi Iida, Takuya Kida, and Hiroki Arimura, “The Relevance Dependent Infinite Relation
Model for Discovering Co-Cluster Structure from Relationships with Structured Noise”, IEICE Trans. Inf.
and Syst., Vol.E99-D, No.4, pp.1139-1152, April 2016. DOI: 10.1587/transinf.2015EDP7329, [JP]165) Shuhei Denzumi, Ryo Yoshinaka, Hiroki Arimura and Shin-ichi Minato: “Sequence Binary Decision
Diagram: Minimization, Relation-ship to Acyclic Automata, and Complexities of Boolean Set Operations,”
Journal of Discrete Applied Mathematics, Vol. 212, pp. 61-80, Oct. 2016. [OV]166) Mayumbo Nyirenda, Ryosuke Omori, Heidi L. Tessmer, Hiroki Arimura, Kimihito Ito, “Estimating the
Lineage Dynamics of Human Influenza B Viruses”, PLoS ONE 11(11): e0166107, 2016. DOI:
10.1371/journal.pone.0166107, (September 2016) [OV]167) Takuya Takagi, Shunsuke Inenaga and Hiroki Arimura, “Fully-online construction of suffix trees for
multiple texts”, Proc. the 27th Annual Symposium on Combinatorial Pattern Matching (CPM'16), Leibniz
International Proceedings in Informatics (LIPIcs), Vol.54, pp.22:1--22:13, DROPS, 2016. (DOI:
10.4230/LIPIcs.CPM.2016.22) (Tel Aviv, Israel, June 27-29, 2016) (Also available as: arXiv:1507.07622)[OV]168) S. Nishimoto, T. Fujisawa, Y. Sasaki, H. Uemura, and K. Saitoh, “Theoretical investigation of six-mode
multi/demultiplexer based on fused-type multicore fiber coupler”, IEEE Photonics Journal, vol. 8, no. 3,
pp. 7802908, June 2016. [OV]169) T. Fujisawa and K. Saitoh, “A group delay spread analysis of strongly coupled 3-core fibers: A effect ofbending and twisting”, Optics Express, vol. 24, no. 9, pp. 9593-9591, May 2016. [OV]170) J. Tu, K. Long, and K. Saitoh, “Design and optimization of 3-mode x 12-core dual-ring structured fewmode multi-core fiber”, Optics Communications, vol. 381, pp. 30-36, Dec. 2016. [OV]171) F. Ye, J. Tu, K. Saitoh, K. Takenaga, S. Matsuo, H. Takara, and T. Morioka, “Design of homogeneous90

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trench-assisted multi-core fibers based on analytical model”, IEEE/OSA Journal of Lightwave Technology,
vol. 34, no. 18, pp. 4406-4416, Sep. 2016. [OV]172) J. Tu, K. Long, and K. Saitoh, “An efficient core selection method for heterogeneous trench-assisted multicore fiber”, IEEE Photonics Technology Letters, vol. 28, no. 7, pp. 810-813, Apr. 2016. [OV]173) Kotoku Omura, Shoichiro Yamasaki, Tomoko K. Matsushima, Hirokazu Tanaka, Miki Haseyama:“Performance Improvement of Error-Resilient 3D DWT Video Transmission Using Invertible Codes”,
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. E99A, no.12, pp.2256-2265 (2016) [JP]174) Takahiro Ogawa, Akihiro Takahashi, Miki Haseyama: “Classifying Insects from SEM Images Based on
Optimal Classifier Selection and D-S Evidence Theory”, IEICE Transactions on Fundamentals ofElectronics, Communications and Computer Sciences, vol. E99-A, no.11, pp.1971-1980 (2016) [JP]175) Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Classification of Gastric Cancer Risk From X-ray
Images Based on Efficient Image Features Related to Serum Hp Antibody Level and Serum PG Levels”,
ITE Transactions on Media Technology and Applications, vol.4, no.4, pp.337-348 (2016) [JP]176) Takahiro Ogawa, Miki Haseyama: “Adaptive Subspace-Based Inverse Projections via Division Into
Multiple Sub-Problems for Missing Image Data Restoration”, IEEE Transactions on Image Processing,vol.25, no.12, pp.5971-5986 (2016) [OV]177) Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “A Web video retrieval method using hierarchicalstructure of Web video groups”, Multimedia Tools and Applications, vol.75, no.24, pp.17059-17079 (2016)[OV]178) Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Estimation of salient regions related tochronic gastritis using gastric X-ray images”, Computers in Biology and Medicine, no.77, pp.9-15 (2016)[OV]179) Takeru Inoue, Hiroaki Iwashita, Jun Kawahara, and Shin-ichi Minato: “Graphillion: software library forvery large sets of labeled graphs,” International Journal on Software Tools for Technology Transfer (STTT),
DOI 10.1007/s10009-014-0352-z, Vol. 18 Issue 1, pp. 57-66, Springer, Feb. 2016. [OV]2-2. Featured in International Conference Proceedings: (Appendix)
2-3. Featured in Japanese Journals: (Appendix)
2-4. Featured in Books Published: (Appendix)

3. Verbal Presentations: #637 in total
3-1. Keynote Speeches: #10 (International #9, Japanese #1)-International Conferences
2019
1)

Masaharu Yoshioka, “GSB Activity Report”, 2021 International Symposium on Big-Data, Cybersecurity
and IoT, March 3-4, 2021, Sapporo [International][Keynote] †91

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2)

Yoshikazu Miyanaga, “Psycho-acoustic Masking Effect for Robust Speech Communication Robot,”
International Conference on Humanoid, Nanotechnology, Information Technology, Communication andControl, Environment, and Management (HNICEM), Nov. 2019. [International][Keynote]

3)

Yoshikazu Miyanaga, “Autonomous ROBOT System with Psycho-acoustic Masking Speech Recognition,”
Regional

ConferenceonComputer

Information

andEngineering(RCCIE),

Nov.

2019.

[International][Keynote]
4)

Yoshikazu Miyanaga, “Psychoacoustic Masking Effect for Noise Robust Speech Recognition Robot,”
Proceedings of 2019 14-th International Symposium on Signals, Circuits, and Systems, IEEE (ISSCS2019,
IEEE), p. 1, Jul. 2019. [doi:10.1109/ISSCS.2019.8801748] [International][Keynote]

5)

Yoshikazu Miyanaga, “Noise Robust Speech Recognition Robot with Psychoacoustic Effect,” Proceedingsof 2019 IEEE International Conference on Consumer Electronics - Asia (ICCE2019-Asia, IEEE), pp. 2930, Jun. 2019. [International][Keynote]
2018

6)

Yoshikazu Miyanaga, “Autonomous ROBOT with Noise Robust Speech Recognition”, International
Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control,
Environment, and Management, IEEE (HNICEM2018, IEEE), Nov. 2018. [International][Plenary
Keynote]7)

Yoshikazu Miyanaga, “Noise Robust Speech Recognition for AI-ROBOT,” International Conference on
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTICON 2018), Jul. 2018. [International][Keynote]8)

Convertino M, Optimal Information Networks: from Data Analysis to Design of Complex Systems,
ISMAC2018 (International Symposium on Multimedia and Communication Technology) August 29-31,
2018, Tottori, Japan [International] [Invited, Keynote]
2016

9)

Miki Haseyama: “Realization of Associative Image Search -Development of Image Retrieval Platform for
Enhancing Serendipity-”, 2016 IEEE 46th International Symposium on Multiple-Valued Logic, pp.56-59(2016) [International][Keynote]-Japanese Conferences
201810) ⻑⾕⼭ 美紀, “AI・IoT・ビッグデータ解析技術による実社会データからの価値創出”, CEVATECHNOLOGY SYMPOSIUM SERIES, Tokyo, Nov. 2018 [Japanese][Keynote]

3-2. Invited Lectures: #104 in total (International #56, Japanese #48)
-International Conferences
2021-2020
1)

Hiroki Arimura, “Interpretable and Explainable Machine Learning for Trustworthy AI”, 2021 International
Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo [International][Invited] *i) †2)

K. Saitoh, “Design of Randomly-Coupled Multicore Fibers”, IEEE Photonics Society Summer Topicals

92

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Meeting Series (SUM), Paper MD3.3, Virtual Conference, July 13-15, 2020. †3)

K. Saitoh, T. Fujisawa, and T. Sato, “Control of Group Delay Spread in Randomly-Coupled Multicore
Fibers”, Optoelectronics and Communications Conference (OECC), Paper T3-1, Taipei, Taiwan, Oct 4-8,
2020. †

4)

K. Saitoh, “Reduction of Group Delay Spread in Coupled Multicore Fibers”, Asia Communications andPhotonics Conference (ACP), Workshop 10, Beijing, China, Oct. 24-27, 2020. †5)

K. Saitoh, “Few-mode Multi-core Fibres: Weakly-coupling and Randomly-coupling”, European
Conference on Optical Communications (ECOC), Paper Tu4A-1, Virtual Conference, Dec. 6-10, 2020. †6)

Hidemi Watanabe, “Single-cell transcriptomics as big data biology”, 2021 International Symposium on
Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo [International][Invited] *i) †7)

Takeo Ohgane, “Recent results on GaBP and AMP for large-scale signal detection”, 2021 International
Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo [International][Invited] *i) †8)Tetsuo Ono, “Intelligent Room using IoT Network and Personal AI Agents”, 2021 International
Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo [International][Invited] *i) †9)Naoki Osada, Whole genome sequencing analysis of house mice across the Eurasian continent. Genome
Concept Centennial Conference. Online international conference, Feb. 17, 2021 †10) Naoki Osada, Inference of East and Northeast Asian Population Histories using Present-day and Ancient
Genome Sequence Data, The First Meeting of the Academic Year 2020 Joint Research Project on “Studies
in Asian and African Geolinguistics”, ILCAA , Oct.10, 2020(Online) †11) Convertino M, Ecosystem connectome: from discovery to Ecosystem Design, Center for EcologicalResearch, Kyoto University, April 2020 [INVITED] †12) Convertino M, ‘’Biocomplexity and Data Science: Critical Interactions from Microbes to Populations in
Ecosystems’’, Environmental Data Science seminar, University of California, Davis, April 2020 (online)[INVITED] †13) Convertino M, Ecosystem Data Science and Design, VinUNI, Vietnam [ONLINE due to COVID-19], June
2020 [INVITED] †14) Convertino M, InTo COVID, Infodemic Tomography: Coupling Covid Social And Epidemiological MediaFor Systemic Risk Management, WHO/SEARO, [ONLINE], August 2020 [INVITED] †15) Convertino M, InTo COVID, Infodemic Tomography: Coupling Covid Social And Epidemiological MediaFor Systemic Risk Management, Central University of Tamil Nadu (India), Sept. 2020 [INVITED] †16) Convertino M, Water Networks as Ecological Corridors: Species, Pathogens, and Populations, Water
Science Forum, Beijing Normal University, [ONLINE due to COVID-19], Sept. 2020 [INVITED] †17) Convertino M, Critical Interactions: Ecosystem Synthesis and Design (from Pathogens to Populations,
Hong Kong Baptist University, Smart Data Society Lab [ONLINE], Sept. 2020 [INVITED] †18) Hiroyuki Iizuka, “Ethogram generation and stereotypy recognition for captive animals using deep learning”,
2021 International Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo[International][Invited] *i) †19) Satoshi Oyama, “Machine Learning with Higher-Order Feature Interactions”, 2021 International

93

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Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo [International][Invited] *i) †20) Hiroshi Tsutsui, “Evaluation of Low Power Consumption Multimedia IoT System Using Zynq UltraScale+
RFSoC”, 2021 International Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo[International][Invited] *i) †21) Toru Ohmoto, “Applied Singularity Theory -- an updated new catastrophe theory”, 2021 International
Symposium on Gig-Data, Cybersecurity and IoT, March 3-4, Sapporo [International][Invited] *i) †22) Naomichi Nakajima and Toru Ohmoto, “Dually Flat Structure for Singular Models”, Workshop on
Stastistical Manifolds and Related Fields (online), Hokkaido University, Dec. 24, 2020. †23) Toru Ohmoto, “Information Geometry from Singularity Theory Viewpoint”, Workshop on Contact
Structure, Singularities and Differetial Equations (online), Jan. 20, 2021. †24) Convertino M, Disaster Information Systems: a Biocomplexity Perspective and Ecosystem Design,
Disaster Prevention Research Institute, Kyoto University, January 2020 [International][Invited]201925) T. Fujisawa, M. Arai, and K. Saitoh, “Epitaxial design of GeSn quantum wells for optoelectronic
applications”, 2019 IEEE Photonics Society Summer Topicals Meeting Series, Paper MA4.1, Miami, USA,
July 8-10, 2019. (July 8) [International][Invited]
26) Masaharu Yoshioka, “Extraction of Knowledge and Information from Documents”, 2019 Summer
International

Symposiumon

Big-Data,

Cybersecurity

and

IoT,

August2019,

Sapporo[International][Invited] *i)27) Takeo Ohgane, “Large-scale signal detection based on belief propagation with node selection”, 2019
Summer International Symposium on Big-Data, Cybersecurity and IoT, August 2019, Sapporo[International][Invited] *i)28) Naoki Osada, “Big data in biology: perspectives of genomic diversity studies”, 2019 Winter International
Symposium on Big-Data, Cybersecurity and IoT, Dec. 2019, Sapporo [International][Invited] *i)29) Convertino M, ‘’Pattern-oriented Metacommunity Modeling: Networks, Uncertainty and OptimalControls’’ and ‘’Reverse Modeling: Information, Possibilities, Systemic Risk and Network Inference’’,Lecturesatthe

UniversityofSurrey(UK),

One

HealthEJP

SummerSchool(https://onehealthejp.eu/summer-school-2019/), August 2019, [International][Invited]
30) Convertino M, “Ecocentric Model-Technology Nexus for EcoHealth”, 2019 Summer International
Symposium on Big-Data, Cybersecurity and IoT, August 2019, Sapporo [International][Invited] *i)31) Convertino M, “Entropy as a Driver of Optimality: Portfolio Effect and Population Connectome’’, Keynote
Lecture The 5th Electronic Conference of Entropy, Session “Biological Systems’’ chaired by Dr. Bill
Sherwin [International] [Invited]32) Convertino M, Mapping the Global Earth Microbiome, Hakubi Center, Kyoto June 2019 [International][Invited]33) Convertino M, Water-Population Nexus for Sustainable Ecosystem Design, School of Civil andEnvironmental Engineering, Nanyang Technological University, Singapore, May 2019 [International][Invited]94

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34) Convertino M, Bio-Hydro-Geo Dynamics: Mapping Systemic Earth Risk, AI for Summit, Seattle, USA,May 2019 [International] [Invited by Microsoft AI for Earth Program]35) Convertino M, A, Environmental Dynamics, Syndemics Prediction and Public Health Control, Chatham
House (The Royal Institute of International Affairs), London, UK, September 2019 [International] [Invited]
36) Convertino M, A, Complex Environmental Dynamics and Population Patterns Prediction, University
College London, Civil and Environmental Engineering Department, London, UK, September 2019
[International] [Invited]37) Hiroyuki Iizuka, “Deep Learning and Big Data for Cognitive Modeling”, 2019 Summer International
Symposium on Big-Data, Cybersecurity and IoT, August 2019, Sapporo [International] [Invited]*i)38) Satoshi Oyama, “Crowdsourcing for Big Data Analytics”, 2019 Summer International Symposium on BigData, Cybersecurity and IoT, August 2019, Sapporo [International][Invited] *i)39) Yoshihiro Hirose, “Geometrical Approach to Data Science”, 2019 Winter International Symposium on BigData, Cybersecurity and IoT, December 2019, Sapporo [International][Invited] *i)40) Manabu Yamamoto: “Development of planar-type ultra-wideband array antennas based on leaf-shaped
radiating elements,” 2019 Winter International Symposium on Big-Data, Cybersecurity and IoT, Hokkaido
University, December 2019. [International][Invited] *i)41) Toru Ohmoto, “Multiple-point formulas revisited” (Feb.13, 2019), International workshop “Kagsohima
Algebra-Geometry-Analysis Seminar”, Feb. 11--15, 2019, Kagoshima University, Japan. [International][Invited, selected]
201842) T. Sakamoto, K. Saitoh, S. Saitoh, Y. Abe, K. Takenaga, A. Urushibara, M. Wada, T. Matsui, K. Aikawa,
K. Nakajima, “120 Spatial Channel Few-mode Multi-core Fibre with Relative Core Multiplicity Factor
Exceeding 100”, European Conference on Optical Communications (ECOC 2018), Paper We3E.5, Rome,
Italy, Sept. 23-27, 2018.[International]
43) T. Fujisawa, T. Sakamoto, T. Matsui, K. Tsujikawa, K. Nakajima, and K. Saitoh, “PLC-based ModeControlling Devices for Mode-Division-Multiplexing”, OptoElectronics and Communications Conference(OECC), Paper 6E1-2, Jeju, Korea, July 2-6, 2018. [International]
44) T. Sakamoto, K. Saitoh, S. Saitoh, K. Shibahara, M. Wada, Y. Abe, A. Urushibara, K. Takenaga, T. Mizuno,
T. Matsui, K. Aikawa, Y. Miyamoto, and K. Nakajima, “Mode Dependent Loss Reduced Few-Mode MultiCore Fiber Design for Repeated Dense SDM Transmission”, OptoElectronics and Communications
Conference (OECC), Paper 5C3-2, Jeju, Korea, July 2-6, 2018.[International]45) T. Sakamoto, K. Saitoh, S. Saitoh, K. Shibahara, M. Wada, Y. Abe, A. Urushibara, K. Takenaga, T. Mizuno,
T. Matsui, K. Aikawa, Y. Miyamoto, and K. Nakajima, “Few-Mode Multi-Core Fiber Technologies for
Repeated Dense SDM Transmission”, IEEE Photonics Society Summer Topicals Meeting Series (SUM),
Paper TuF2.2, Waikoloa, Hawaii, USA, July 9-11, 2018.[International]46) Toru

Ohmoto, “Multiple-point formulas revisited”(Oct. 5, 2018), International workshop “Singularities

and Characteristic classes/RR50”, Oct. 4--6, 2018,

University of Geneva, Switzerland.

[International][Invited, selected]

95

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201747) K. Saitoh, T. Fujisawa, and T. Sato, “Weakly-coupled and strongly-coupled multicore fibers”,
OptoElectronics and Communications Conference (OECC), Paper Oral 2-3B-2, Singapore, July 31-Aug 4,
2017. [International](Invited) (Aug. 2)48) K. Saitoh, T. Fujisawa, and T. Sato, “Design and analysis of weakly- and strongly-coupled multicore fibers”,
OSA Advanced Photonics Congress (APC), Paper NeTu2B.5, New Orleans, USA, July 24-27, 2017.
[International](Invited) (July 25)49) T. Fujisawa and K. Saitoh, “Material analysis of GeSn/SiGeSn quantum wells based on many-body theory”,
IEEE Photonics Society Summer Topicals Meeting Series (SUM), Paper TuA1.1, San Juan, Puerto Rico,
July 10-12, 2017. [International](Invited) (July 11)
201650) K. Saitoh, “Multicore fibers for high density space division multiplexing”, 11th International Workshop on
Optical Signal Processing and Optical Switching (IWOO), Sapporo, Japan, Nov. 16-17, 2016.
[International]
51) T. Sakamoto, T. Matsui, K. Saitoh, S. Saitoh, K. Takenaga, and S. Matsuo, Y. Tobita, N. Hanzawa, K.
Nakajima, F. Yamamoto, “High spatial density few-mode multi-core fiber for dense space divisionmultiplexing transmission”, Photonic Networks and Devices, Paper NeW2C.3, Vancouver, Canada, July
18-20, 2016.[International]
52) K. Aikawa, Y. Sasaki, Y. Amma, K. Takenaga, S. Matsuo, K. Saitoh, T. Morioka, and Y. Miyamoto, “Highcore count single-mode multicore fiber for dense space division multiplexing”, IEEE Photonics Society
Summer Topicals Meeting Series (SUM), Paper WE2.2, Newport Beach, USA, July 11-13,
2016.[International]
53) K. Saitoh, “Multicore multimode fibers with high spatial density”, IEEE Photonics Society Summer
Topicals Meeting Series (SUM), Paper TuE4.1, Newport Beach, USA, July 11-13, 2016. [International]
54) T. Sakamoto, T. Matsui, K. Saitoh, S. Saitoh, K. Takenaga, S. Matsuo, Y. Tobita, N. Hanzawa, K. Nakajima,
F. Yamamoto, “High spatial density few-mode multi-core fiber with low differential mode delay
characteristics”, OptoElectronics and Communications Conference (OECC), Paper MC2-3, Niigata, Japan,
July 3-7, 2016.[International]55) Y. Sasaki, Y. Amma, K. Takenaga, S. Matsuo, K. Aikawa, K. Saitoh, T. Morioka, and Y. Miyamoto, “Singlemode multicore fiber for dense space division multiplexing”, OptoElectronics and Communications
Conference (OECC), Paper MC1-4, Niigata, Japan, July 3-7, 2016. [International]
56) Shin-ichi Minato: “Power of Enumeration - BDD/ZDD-Based Techniques for Discrete Structure
Manipulation,” In Proc. of IEEE 46th International Symposium on Multiple-Valued Logic (ISMVL2016),
p. 143, May 2016. [International][Invited]-Japanese Conferences
2021-202057) ⿑藤晋聖, “⼤容量空間分割多重伝送⽤光ファイバーの最新動向,” 第 156 回微⼩光学研究会「オンライン社会を加速する光通信と微⼩光学」, オンライン, Oct. 14, 2020. †96

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2021/11/12 9:4458) ⻑⾕⼭ 美紀: "データサイエンス教育のフロンティア", NoMaps Conference 2020 (2020) [JP]59) ⻑⾕⼭ 美紀: "データサイエンス基礎から応⽤", 放送⼤学講義 (2020) [JP] †60) ⻑⾕⼭ 美紀: "第 3 次 AI ブームを考える - 情報科学を駆使した実社会データ連携 -", ソフトウェア
シンポジウム (2020) [JP] †61) ⻑⽥直樹, ⽇本⼈のルーツと病気とのかかわり，NHK カルチャーヤマト王権・古代史講座特別編ー
⽇本列島⼈の起源と歴史，オンライン講座，2020 年 9 ⽉ 27 ⽇†
62) 筒井弘, 無線通信・画像処理ハードウェア IP の設計技, IEEE Sapporo Section YP Invited Talk,
Muroran Institute of Technology, December 18, 2020, †63) ⽇景隆，吉江明花，⼤宮

学: “［依頼講演］⼤規模 FDTD 解析を⽤いた都市環境モデルの 3 次元

伝搬特性推定”，信学技報, vol. 120, no. 97, AP2020-9, pp. 1-4, 2020 年 7 ⽉. †64) 吉江明花，佐藤亜⾐，⽇景

隆: “［依頼講演］市販レイトレーシングソフトを⽤いた都市環境伝搬特性シミュレーションの⾼速化検討”，信学技報, vol. 120, no. 97, AP2020-10, pp. 5-7, 2020 年 7 ⽉. †65) ⽇景隆: “ペースメーカ等医療機器と EMC の話題”，IoT 時代のシステムと EMC 調査専⾨委員会(電気学会)，オンライン，2020 年 10 ⽉. †66) ⽇景隆: “電波と⽣体安全性-基本的考え⽅から実際の評価まで-”，第 26 回 EMC 環境フォーラム，技術セッション 9「電波と⽣体安全性」，オンライン，2020 年 10 ⽉. †67) ⻑⾕⼭ 美紀: “AI・ビッグデータ解析に基づいた実観測データからの価値創出”フォトエキサイトニ
クス研究拠点第２回研究会（2020）[JP][Invited]201968) ⿑藤晋聖, 藤澤 剛, “データセンタ間通信における SDM 技術の適⽤可能性”, 電⼦情報通信学会ソサイエティ⼤会, BCI-1-6, ⼤阪, Sep. 10-13, 2019. (Sep. 11) [JP] [Invited]69) 藤澤 剛, 澤⽥祐甫, ⿑藤晋聖, “最適化⼿法を⽤いたモード分割多重通信向け光導波路デバイスの研究”, 電⼦情報通信学会ソサイエティ⼤会, C-3-27, ⼤阪, Sep. 10-13, 2019. (Sep. 12) [JP][Invited]70) ⾼野純⽮, 藤澤 剛, 澤⽥祐甫, 坂本泰志, 松井 隆, 中島和秀, ⿑藤晋聖, “シリコンフォトニクスによる⾼次モードを⽤いた低損失かつ⾼トレランス 100/400GbE ⽤ 4 波⻑合波器”, C-3-57, ⼤阪,
Sep. 10-13, 2019. (Sep. 13) [JP][Invited]71) 藤澤剛, ⿑藤晋聖, “最適化⼿法を⽤いた空間分割多重通信向け光導波路デバイスの研究,” 第 152 回
微⼩光学研究会 “AI で拡げる微⼩光学”, 東京 June 14, 2019.[JP] [Invited]72) ⻑⾕⼭ 美紀: “AI の進化と⼈間の可能性” 札幌⼤⾕中学校（2019）[Invited]73) ⻑⾕⼭ 美紀, ⼩川 貴弘: “⽣体情報解析を導⼊した次世代 AI 技術の構築” 電⼦情報通信学会通信
ソサイエティ⼤会 (2019) [Invited]74) ⻑⾕⼭ 美紀: “AI・IoT・ビッグデータ解析による次世代インフラ維持管理に向けた取り組み” 第 29
回トンネル⼯学研究発表会（2019）[Invited]75) ⻑⾕⼭ 美紀: “データサイエンスの未来” Junior Programming World 2019(2019) [Invited]76) ⻑⾕⼭ 美紀: “AI・IoT・ビッグデータ解析に基づいたマルチメディア信号処理による実社会データからの価値創出” 映像情報メディア学会

冬季⼤会 2019（2019）[Invited]77) ⻑⾕⼭ 美紀: “画像処理で広がる未来〜わくわくする未来につながる最先端研究〜” AI とデータサイ
エンスを知って親しむ講義×体感イベント（2019）[Invited]

97

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78) ⼤鐘 武雄, “ガウス確率伝搬法等繰り返し⼿法を⽤いた多数信号検出特性” 無線電信システム研究会（RCS），沖縄県宮古島，2019 年６⽉ 20 ⽇（招待講演）
79) ⼤鐘 武雄, “スマートアンテナ技術「MIMO」の最新動向”, ワイヤレス・テクノロジー・パーク(WTP)2019，東京ビッグサイト，2019 年５⽉ 31 ⽇（招待講演）

201880) R. S. Luis, G. Rademacher, B. J. Puttnam, T. A. Eriksson, 古川英昭, A. Ross-Adams, S. Gross, M.
Withford, N. Riesen, 佐々⽊雄佑, ⿑藤晋聖, 愛川和彦, 淡路祥成, 和⽥尚也, “C+L 帯 368 波⻑
PDM-256-QAM 信号を⽤いた 160 um クラッド径 4 コア 3 モードファイバによる 1.2 Pb/s 伝送 〜
ECOC2018 ポストデッドライン論⽂報告 〜”, 電⼦情報通信学会光通信システム研究会, OCS201865, 東京, Nov. 12, 2018.[Japanese]81) ⿑藤晋聖, “空間分割多重伝送⽤光ファイバの現状と課題”, 電⼦情報通信学会フォトニックネットワ
ーク研究会，PN2018-18, 帯広市, Sep. 3-4, 2018.
82) ⿑藤晋聖, “空間分割多重伝送のためのマルチコア／マルチモードファイバ”, 技術レーザー学会「ファイバーレーザー技術」専⾨委員会第２回委員会, 千歳市, July 26-27, 2018.
83) ⿑藤晋聖, “空間分割多重伝送のための光ファイバ技術”, 電⼦情報通信学会光ファイバ応⽤技術研究会創⽴ 20 周年記念シンポジウム, OFT-T1, 東京, May 17, 2018.
84) 芝原光樹, ⽔野隆之, 李⽃煥, 宮本裕, ⼩野浩孝, 中島和秀, ⻫藤翔太, ⽵永勝宏, ⿑藤晋聖, “モード間⼲渉キャンセラを⽤いた 2500km-12 コア x3 モード多重ファイバ及び 6300km-3 モード多重
ファイバのモード分散⾮マネジメント空間多重伝送”, 電⼦情報通信学会光通信システム研究会,
OCS2018-7, 東京, May 11, 2018.
85) ⿑藤晋聖, 藤澤

剛, ⽵永勝宏, 愛川和彦, 坂本泰志, 松井隆, 中島和秀, “⾼密度空間分割多重マ

ルチコアファイバの設計技術”, 電⼦情報通信学会光通信インフラの⾶躍的な⾼度化に関する研究会,
EXAT2017-13, 那覇市, Feb. 15, 2018.
86) ⼩川 貴弘, ⻑⾕⼭ 美紀: “低次元画像近似に基づいたインペインティングとその⼯学的応⽤”, 電⼦
情報通信学会技術研究報告, vol.118, no.147, pp.1-4 (2018) [Invited]87) ⻑⾕⼭ 美紀,

住友ゴム⼯業株式会社にて講演(2018) [Invited]88) ⻑⾕⼭ 美紀, 室蘭⼯業⼤学にて講演(2018) [Invited]89) ⻑⽥直樹, “ゲノムからたどる⼈類進化の歴史”, 名古屋⼤学遺伝⼦実験施設公開セミナー「ゲノム解析が⾒える化する⽣命の成り⽴ち」, 名古屋⼤学，名古屋市

2018 年 12 ⽉ 10 ⽇ 招待講演

201790) ⿑藤晋聖,”Multicore Fiber Technology for Space Division Multiplexing (SDM)”, 第 31 回 光通信シ
ステムシンポジウム, 三島市, Dec. 19-20, 2017. (Dec. 20)91) ⿑藤晋聖, “空間分割多重伝送の現状とモード制御デバイス”, 集積光デバイスと応⽤技術研究会，
IPDA17-2-11, 加賀市, Nov. 9-10, 2017. (Nov. 10)92) 藤澤剛, 荒井昌和, ⿑藤晋聖, “中⾚外フォトニクス向け GeSn 系量⼦構造と光デバイス応⽤”, 電

⼦情報通信学会ソサイエティ⼤会, C-4-10, 東京, Sep. 12-15, 2017 (Sep. 13)（依頼講演）
93) ⽯坂雄平, 藤澤

剛, ⿑藤晋聖, “屈折率センサの⾼感度化に向けたプラズモニック導波路構造の検討”, 電⼦情報通信学会ソサイエティ⼤会, C-3-8, 東京, Sep. 12-15, 2017 (Sep. 12)（依頼講演）

98

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2021/11/12 9:4494) ⻑⾕⼭ 美紀: “［特別招待講演］ビッグデータからの価値創出を実現する次世代情報検索 〜AI・IoT
技術の発想⽀援型検索への導⼊〜”, 電⼦情報通信学会技術研究報告, vol.117, no.329, pp.101-106(2017) [Invited]95) ⻑⽥直樹, “集団遺伝学とゲノム進化学”, 第 11 回⽣物学基礎論研究会特別講演, 札幌市北海道医療⼤学札幌サテライトキャンパス, 2017 年 9 ⽉ 10 ⽇

招待講演

2016
96) ⽔野隆之, 芝原光樹, ⼩野浩孝, 阿部宜輝, 宮本裕, フェイフォン イェ, 盛岡敏夫,佐々⽊雄佑, 安間淑通, ⽵永勝宏, 松尾昌⼀郎, 愛川和彦, 齋藤晋聖, ヨンミン ジュン, デイビッド リチャードソン, “32 コアファイバによる⾼密度空間分割多重（DSDM）光伝送技術〜 OFC2016 ポストデッドライン報告 〜”, 電⼦情報通信学会光通信システム研究会，OCS-2016-7, 東京，May 13, 2016．(May13)97) ⻑⾕⼭ 美紀: “社会インフラの維持管理におけるビックデータ時代の到来”, ⼟研

新技術ショーケース 2016 in 札幌 (2016) [Invited]98) ⻑⾕⼭美紀: “情報科学に基づいた社会インフラメンテナンス⾼度化の試み”, 第 11 回産学官 CIMGIS
セミナー (2016) [Invited]99) ⻑⾕⼭ 美紀: “ビッグデータからの価値創出を実現する発想⽀援型検索 〜バイオミメティクス画像
検索基盤への応⽤〜”, 2016 年電気化学会北海道⽀部・東海⽀部合同シンポジウム 「インテリジェ
ント電気化学の新潮流」, pp.11 (2016) [Invited]100)⻑⾕⼭ 美紀: “ビッグデータ時代の発想⽀援型画像検索 〜 ⽣物の微細構造が有する機能の発⾒法 〜”, ⽇本⽐較⽣理⽣化学学会 東京⼤会 (2016) [Invited]101)

⾼橋 翔，⻑⾕⼭ 美紀: “サッカー映像における試合内容の理解を促すデータの可視化”, 映像情報メディア学会年次⼤会, pp.S4-6 (2016) [Invited]102)⻑⾕⼭ 美紀: “[招待講演]マルチメディア信号処理と次世代情報検索”, 電⼦情報通信学会技術報告, vol.116, no.166, pp.33-36 (2016) [Invited]103)⻑⾕⼭ 美紀: “気づきを⽣み出す発想⽀援型検索 −ビッグデータからの価値創出−”, ITpro

EXPO 2016 (2016) [Invited]104)⻑⾕⼭ 美紀: “報技術による社会インフラ管理の⾼度化 −ビッグデータ解析による構造物点検の⾼精度化の試み−”, CReC シンポジウム (2016) [Invited]

3-3. Other Presentations: #523

4. Patent Applications: #16 (Registered Patents #7) in total
Overseas Patents: # 4 (#1), Japanese Patents: # 12 (#5)
-Overseas Patents
1)

International Patent, Application No. PCT/JP2018/025024, Information transmission system, Jan. 9, 2020,
Hokkaido University, Masanori Sugimoto2)

US Patent 9858661B2, Detecting species diversity by image texture analysis, 2018, The Charles Stark

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Draper Laboratory, Inc., University of Florida Research Foundation, Inc., Charles Stark Draper, M
Convertino and R Mangoubi
3)International Patent Application No. PCT/JP2018/003039, (WO2018/150867), Multicore fiber andmulticore fiber tape using same, 2018 January, Fujikura Ltd., Hokkaido University, Technical Universityof Denmark, Yusuke Sasaki, Kunimasa Saitoh, Toshio Morioka et al.

4)International Patent Application No. PCT/JP2017/008307, (WO2017/159385), Multicore fiber, 2017
March, Nippon Telegraph and Telephone Corporation, Hokkaido University, Taiji Sakamoto and Kunimasa
Saitoh et al.
-Japanese Patents

5)Japanese Patent No. 6781432 (P6781432), “A method for producing a radio wave propagation simulation
model creation system, creation apparatus and creation program”, 2020 Oct., Hokkaido University and
NIPPON TELEGRAPH AND TELEPHONE CORPORATION, Inomata, Kimoto, Nakamura, Takatori,
and Hikage

6)Japanese Laid-Open Patent Publication No. Tokkai 2020-005233, Phased array antenna system, 2020
January, Takashi Hikage, Manabu Yamamoto

7)

Japanese Patent No. 6609387, Method, system and program for estimating properties of rubber materials,
2019, Hokkaido University and Sumitomo Rubber Industries, Ltd., Miki Haseyama, Takahiro Ogawa,
Hiroaki Yamada, Wakana Ito

8)Japanese Patent No. 6609388, Diagnostic device for rubber material deterioration, 2019, Hokkaido
University, Sumitomo Rubber Industries, Ltd., Miki Haseyama, Takahiro Ogawa, Hiroaki Yamada, Wakana
Ito

9)Japanese Patent Application No. Tokugan 2019-201196, Positioning system, positioning method, signal
generator, signal receiver and control program, Nov. 6, 2019, Hokkaido University, Masanori Sugimoto10) Japanese Laid-Open Patent Publication No. Tokkai 2020-046623, Few-mode multicore optical fiber, 2018
September, Nippon Telegraph and Telephone Corporation, Hokkaido University, Taiji Sakamoto andKunimasa Saitoh et al.
11) Japanese Laid-Open Patent Publication No. Tokkai 2020-027216, Mode multi/demultiplexer, 2018 August,
Nippon Telegraph and Telephone Corporation, Hokkaido University, Taiji Sakamoto and Kunimasa Saitoh
et al.
12) Japanese Laid-Open Patent Publication No.Tokkai 2019-191224, Mode exchanger, 2018 April, Nippon
Telegraph and Telephone Corporation, Hokkaido University, Taiji Sakamoto and Kunimasa Saitoh et al.
13) Japanese Laid-Open Patent Publication No. Tokkai 2019-152717, Wavelength multiplexer, 2018 March,
Nippon Telegraph and Telephone Corporation, Hokkaido University, Taiji Sakamoto and Kunimasa Saitoh
et al.
14) Japanese Patent No. 6631848, Mode multi/demultiplexer and mode division multiplexed transmission
system, 2017 March, Nippon Telegraph and Telephone Corporation, Hokkaido University, Taiji Sakamoto
and Kunimasa Saitoh et al.
15) Japanese Patent No. 6699028, Mode exchanger, 2017 March, Nippon Telegraph and Telephone100

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Corporation, Hokkaido University, Taiji Sakamoto and Kunimasa Saitoh et al.
16) Japanese Patent No. 6653886, Mode multi/demultiplexer and mode division multiplexed transmission
system, 2016 September, Nippon Telegraph and Telephone Corporation, Hokkaido University, Taiji
Sakamoto and Kunimasa Saitoh et al.
5. Awards Received: (Awards at International Conferences are listed in Appendix)

6. External Grants: #67 in total
Collaborative Research between HU and Overseas Members: #3, Others: #64
1)

Fund for the Promotion of Joint International Research (Fostering Joint International Research (B)) ,“Multi-Media IoT based on Energy Harvest Cognitive Wireless Network”, February 2019 – March 2021),
Yoshikazu Miyanaga (HU, PI), Manabu Yamamoto (HU, co-investigator), Takashi Hikage (HU, coinvestigator), Negin Shariati Moghadam (UTS, co-investigator) and Xiaojing Huang (UTS, international
collaborator), 13,600,000 yen. @GI-CoRE

2)

Grant-in-Aid for Scientific Research (B), “Research on analysis and visualization of news websites stancebased on the comparison among various news websites”, FY 2018 – 2021 (4 years), Masaharu Yoshioka(HU, PI), James Allan (UMass Amherst, collaborative researcher), 17,030,000 yen. @GI-CoRE

3)

Australian-Japan Foundation, DFAT, “Promoting Wagyu Beef Traceability between Japan and Australia”,
September 2019 – June 2021, Ying He (UTS, PI), Hiroshi Tsutsui (HU, research participant), 20,000
Australian dollars. @GI-CoRE

(end)

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e. Utilization and dissemination of research achievements
1．
．Organization of international symposiums
1) August 31 – September 2, 2016: International Symposium on Multimedia and Communication Technology,
ISMAC 2016 (Tokyo City University, Tokyo), cohosted by IEICE and the GSB● Dispatch of Lecturer Negin Shariati (a UTS researcher with a cross-appointment) as a keynote speaker● Participation of three HU professors (GSB members)● Two presentations by students (research assistants)
2) August 23 – 25, 2017: 2017 International Symposium on Multimedia and Communication Technology,
Ayutthaya, a World Heritage historic city of Thailand, cohosted by IEICE, ECTI and the GSB● Tutorial lecture by an HU professor (GSB member)● One presentation by a student (research assistant)3) August 29 – 31, 2018: International Symposium on Multimedia and Communication Technology, (ISMAC
2018), Tottori, Japan, cohosted by IEICE, ECTI, APSIPA and GSB● Dispatch of Lecturer Negin Shariati (UTS researcher with a cross-appointment) as a plenary speaker● Dispatch of Associate Professor Matteo Convertino (GSB HU member) as a keynote speaker● Participation of an HU professor (GSB member)● Three presentations by students (research assistants)
4) August 19 – 21, 2019: International Symposium on Multimedia and Communication Technology, (ISMAC
2019), Manila, Philippines, hosted by IEEE, IEICE, ECTI and the GSB● Dispatch of Professor Eryk Dutkiewicz (a UTS researcher with a cross-appointment) as a keynote speaker● Participation of an HU professor and a HU associate professor (GSB members)● Three presentations by students (research assistants)
2. Extension lectures and exhibition for the general public
1) Lecture and exhibition at ITpro Expo Sapporo 2016
2) Extension lectures on cybersecurity and big data science for the general public (October – November 2016)
3) May 26, 2019: Hokkaido University and Citizen’s College of Hokkaido Extension Lecture “Artificial
Intelligence and Big Data,” cohosted● Lecture cohosted by IEEE and the GSB in line with IEEE ISCAS 2019
f. Issues in conducting research, their solutions and future development
Mutual understanding of research is indispensable for conducting specific collaborative research, and thisrequires close exchanges of opinions over an extended period (at least two weeks to one month). However, it
45

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may be difficult for researchers with cross-appointments who have many students at their own universities toleave their universities even for a short period. As a result, it is hard for them to finish their collaborative
research while staying at Hokkaido University.
In addition to overseas researchers with cross-appointments coming to Hokkaido University, the GSB has
dispatched associate professors who have relatively few students and doctoral students from Hokkaido
University to partner universities for collaborative research.
Some dispatched professors have started researchers from the discussions during their stay at UMass Amherst
and UTS. Some doctoral students started research during their stay at an overseas university and continued itafter returning to Japan by utilizing various online tools, such as e-mail and tools for co-authoring papers, andhave presented a refereed paper at international conferences. This experience showed that dispatched students
can experience an international research environment and achieve successful results if themes and faculty
members at host universities are appropriately determined. In the future, researchers with cross-appointments
may want to serve as a contact point and help to create a framework for matching dispatched students withappropriate faculty members at host universities to provide a better research and education environment for
doctoral students.
Meanwhile, the spread of remote conference systems in recent years has facilitated collaboration between
overseas researchers with cross-appointments and the faculty of Hokkaido University, reducing the barriers forteaching remotely without leaving their home universities. In the future, the GSB would like to promote
practical exchanges while utilizing such technologies.
2. Education (International Graduate School)
2.1 Objective
Regarding the social background to the information science field, information science and technology are
utilized in all fields of social and economic activities, and social and economic activities themselves are built
on the Internet, creating a virtual society (cyber space). This trend is spreading all over the world and is referred
to as an IT revolution or an Internet revolution.
The Fifth Science and Technology Basic Plan (decided by the Cabinet on January 22, 2016) highlights
weakened fundamentals and the fact that industry-academia collaboration has yet to reach full maturity. It
recommends the reinforcement of fundamentals involved in science, technology and innovation, theenhancement of competitiveness in a “super smart society” and the strategic strengthening of fundamental
technologies. Cybersecurity, IoT system construction, big data science, AI, devices, robots, sensors,biotechnology, material/nanotechnology, and light/quantum are listed as fundamentals. In addition, support for
researchers working overseas, the construction of international research networks, and the mobilization ofhuman resources across fields, organizations and sectors are cited as examples of strategic strengthening.
Similarly, at the 10th meeting of the Council on Investments for the Future (June 2017), it was thatmathematical and big data science education should be promoted university-wide, in all humanities or science
courses. In both of the above cases, the importance of the new information science fields and the role ofuniversities that support them are highlighted.

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At the same time, a report on ideal engineering education at universities (interim summary) (June 2017, Study
Committee on Ideal Engineering Education at Universities, Ministry of Education, Culture, Sports, Science andTechnology) highlights the importance of a drastic review of the vertical division structure of each department,
the learning of minor fields in addition to the major field, the strengthening of basic engineering education, theenhancement of common basic education in engineering and information science and technology, thereinforcement of advanced information human resource education, and the establishment of an industryacademia collaborative education system.
Meanwhile, according to data from the New Industrial Structure Subcommittee of the Industrial Structure
Council at the Ministry of Economy, Trade and Industry (13th meeting, February 13, 2017), the shortage ofhuman resources in information science is serious, and there is currently a shortage of approximately 171,000
engineers and researchers. It is estimated that there will be shortages of roughly 369,000 in 2020 and 789,000
in 2030.
Accordingly, for higher education to meet the demands of society, it must develop outstanding humanresources by reforming the vertical structure of academic disciplines, which has been maintained for many years,
and creating an interdisciplinary information science education system that meets the needs of the times. Thisrequires the prompt development of human resources that can adapt to the new age through new education basedon e-learning that can support lifelong learning and through a multi-field curriculum (students take subjects
provided in their specialized course and other courses.) that can promote interdisciplinary research anddevelopment. There seems to be a demand for individuals who can practically utilize IT capabilities from a
global perspective beyond the boundaries of education and research fields.
One of the goals of the Future Strategy for the 150th Anniversary of Hokkaido University, which wereannounced in August 2014, is to promote world-leading research to resolve a variety of issues to create asustainable society for the next generation. The basis of the plan is to “prepare an environment suitable forcutting-edge international collaborative research that brings together top researchers from around the world, andconstruct a world-class center for global brain circulation.” To achieve this goal, the GI-CoRE has been
established to form international collaboration with top-class overseas universities and to create a research andeducation hub at Hokkaido University.
In 2016, the GSB was established as a part of GI-CoRE, and the Graduate School of Information Science andTechnology functions as the organizing department. The goal of the GSB is to build a global brain circulation
center and to develop individuals who can contribute to the resolution of social issues. To achieve this goal, it
is necessary to reform graduate school education on the back of international collaboration, and the Graduate
School of Information Science and Technology is part of this concept of international collaboration.
In the redefinition of the University’s mission (presented in November 2013), the Graduate School ofInformation Science and Technology is highly regarded for: 1) further promoting world-leading research in theinterdisciplinary research area centered on information, 2) contributing to the development of industrial
technology by utilizing its proven track record in commissioned research and collaborative research and bycollaborating with domestic and overseas industries, research institutes and other universities, and 3)
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contributing to the re-learning and skill improvement of working adults by providing various learning
opportunities based on a good record in admitting working adults from Hokkaido and elsewhere in the doctoral
program.
Based on these achievements, educational strategies have been plotted to develop industry-ready practicalengineers in the short term, and in the long term to cultivate future-oriented innovation leaders (IL) and frontier
leaders (FL) who can be active globally.
The development of practical engineers (professional engineer development) means to develop engineers who
can provide solutions to the social problems using big data science approach and realization of cybersecurity
for the devices and software of the current network.
The cultivation of innovation leaders means to cultivate individuals who can solve such problems throughpractical experience that leads to create new knowledge, while the cultivation of frontier leaders means tocultivate individuals who study technologies that can respond to ill-defined problem such as unknown
cyberattacks and other problems happened in the new network society.
Regarding cybersecurity education, education programs are developed based on the global interuniversity
network. At the undergraduate level, with the aim of developing industry-ready practical engineers, short-term
education programs are provided utilizing short-term seminars and e-learning suitable for the re-learning ofworking adults. At the graduate level, in the master's program, students may acquire basic credits from otherschools, such as engineering, medicine, science and humanities, and receive project management (PM) lecturesthat include problem-based learning (PBL). Although focus is placed on practical science, innovation leaders
are also developed so that cyber informatics experts can play active roles in various sectors. In the doctoral
program, research supporting new fields is promoted centered on a multi-field curriculum in cybersecurity, bigdata science and information network engineering, to develop frontier leaders suitable for international research
activities.
2.2 Progress and future developmenta. Education implementation structure (organization)
As stated in the redefinition of the mission in the engineering field of the University, the Graduate School ofInformation Science and Technology has actively involved in interdisciplinary research and has world-leading
track records in big data science, such as the world's fastest data processing record. Moreover, the school has
world-class records in information and communication networks that support IoT, such as the research anddevelopment of optical fibers that realize the world's largest communication capacity.
Concerning information science education in the University, the Department of Electronics and Information
Engineering (180 students) at the School of Engineering has five courses: the Course of Computer Science andInformation Technology (50 students), the Course of Electrical and Electronic Engineering (40 students), theCourse of Bioengineering and Bioinformatics (33 students), the Course of Media and Network Technologies
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(30 students), and the Course of Systems, Control and Electrical Engineering (27 students). In the Graduate
School of Information Science and Technology (quota: master’s: 177, doctoral: 42), there were the following
specialties corresponding to the above five courses when the GSB was established: Computer Science andInformation Technology (quota: master’s: 48 + doctoral: 12), Electronics for Informatics (quota: master’s: 39 +doctoral: 8), Bioengineering and Bioinformatics (quota: master’s: 33 + doctoral: 6), Media and Network
Technologies (quota: master’s: 30 + doctoral: 8) and Systems Science and Informatics (quota: master’s: 27 +doctoral: 8). At that time, more students than the quota were often admitted, and students who completed theirgraduate studies have been employed by more than 200 research institutes and companies in Japan andelsewhere (employment rate: 97% (master's), 91% (doctoral), or more).
In addition, the Information Initiative Center and Hokkaido University Hospital have the most successful
track records in the practical use of academic and medical big data in Japan, and have conducted cybersecurity
demonstration experiments using the largest academic cloud system in Japan. This project promotes the research,development and practical use of medical big data systems for the creation of clinical bioinformatics aiming toindividualize medical care through international and interdepartmental collaboration.
In order to develop various human resources involved in big data science, cybersecurity and IoT, the previous
Graduate School of Information Science and Technology has been reorganized into the Faculty of Information
Science and Technology, which is a research organization to which faculty members of the previous Graduate
School of Information Science belong, and the new Graduate School of Information Science and Technology,
which consists of faculty members of other departments, including researchers with cross-appointments.
Thus, a new global station, GSB has been established in the GI-CoRE, an organization under direct controlof the President, by merging world-leading education and the research units of overseas universities with the
University's researcher group and domestic collaborative institutions.
The Graduate School of Information Science and Technology aims to develop IT professionals in big data
science and cybersecurity based on the research results generated by conducting advanced international
collaborative research at the GSB, and to function as an international educational organization in the information
science-related field, which already has high social needs. Therefore, the Graduate School of Information
Science and Technology achieves an interdisciplinary education system not only with members of the Facultyof Information Science and Technology and researchers with cross-appointments but also with personnel
support from other departments in the University (the Information Initiative Center and the Faculty of Science)and collaboration and cooperation in curriculum development from the humanities fields, including the
Graduate School of Law. Specifically, a graduate school preparatory committee was launched in FY 2017 to
begin studies. In 2018, an application for establishing the school was made to the Evaluation Committee for theChartering of Universities and it was approved. In 2019, the previous graduate school was reorganized into the
Faculty of Information Science and Technology and the Graduate School of Information Science andTechnology. Coupled with that, a new graduate school was established (quota: master’s: 179, doctoral: 43),
where a program to develop frontier leaders and innovation leaders has been conducted.
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At the new Graduate School of Information Science and Technology, researchers with cross-appointments
teach seven international collaborative informatics subjects related to big data science, security technology andIoT technology in English, allowing students to earn credits and develop an international perspective by taking
such subjects in English.
The existing Meme Media Laboratory, a Hokkaido University Collaborative Project Center, has worldleading track records in research and development in big data science, and is sharing human resources, hardware
and software equipment in this project, which is aimed at interdisciplinary research on big data science andcybersecurity.
b. Education implementation structure (system)
The following is an outline of the newly established Division of Information Science and Technology. The
previous Graduate School of Information Science and Technology, which was comprised of five divisions, wasreorganized into the new graduate school with one division. In the division, students can acquire broad basic
knowledge in relevant fields through expanded common subjects. By preparing international collaborative
informatics subjects, the graduate school provides global interdisciplinary collaborative education based onhighly specialized knowledge in each field and allows students to acquire practical knowledge corresponding
to the needs of society and practical skills as global leaders.
Five courses have been established in the division to cultivate excellent researchers who lead global
development using advanced expertise in five information science research fields. This allows the graduate
school to provide cutting-edge specialized education in these individual research fields and allows students toacquire world-leading research skills.
Each course provides specialized subjects, and students who belong to the course take the subjects as theirmajor. At the same time, they take subjects of other courses as their minor. Therefore, in the master's program,a multi-field curriculum is employed, where students learn major and minor course subjects. In addition,
students in the doctoral program take a third specialized subject in addition to the subjects they have studied in
the master’s program. However, for a student who wants to engage in international collaborative education,practical education, and integrated education in the humanities and sciences, as well as boundary research, theirsupervisor will consider the relevance to the student's research theme and discuss with co-supervisors so thatthe student can study subjects flexibly. In order to realize such a variety of study patterns, international
collaborative informatics subjects, practical subjects, and integrated subjects in the humanities and sciences areoffered as common subjects.
The Division of Information Science and Technology provides careful and effective research guidance.
Students of each course can receive guidance from faculty members who belong to the Faculty of Information
Science and Technology, the Faculty of Science and various centers. At the same time, faculty members fromdifferent departments, the GSB, centers, and research institutes teach students as co-supervisors. For example,
regarding the research “Big Data Analysis of Human-Animal- Ecosystems Using Sustainable IoT Network
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Technology for Community Management” as a master's thesis, a supervisor from the media network fieldteaches the student with GSB members as co-supervisors.
In the master's program, research guidance is provided through collaboration between the supervisor and one
or more co-supervisors, and in the doctoral program, a research guidance committee comprised of the supervisor
and multiple co-supervisors is formed to provide guidance. Such research guidance is appropriately and flexibly
implemented not only by members of the Faculty of Information Science and Technology but also by otherresearchers according to the research theme of students.
c. Admission of students
The Graduate School of Information Science and Technology admits students who have a strong will to obtaina master's degree or a doctorate in the field of information science, and who aim to study the information sciencefield in a broad sense, including electrical engineering, electronic engineering, system engineering,mathematical science, biological engineering, life science and social science.
The basic concept of admitting new students in the master's and doctoral programs of the new graduate schoolis as follows:
Master's program: The school admits graduates from universities in Japan and elsewhere (including prospective
graduates) who aim to conduct research and development in the information science field in a broad sense as
their own career. Specifically, they should be students in Japan and elsewhere who wish to major in the field of
information science and obtain a master's degree. By introducing various entrance examination systems, theschool actively admits interdisciplinary students who transcend the majors of technical colleges and specialized
fields at universities and international students. For the entrance examination of the master's program, aspecialized examination is conducted in English or Japanese. The specialized examination consists of a written
test (paper) and an oral test to gauge the proficiency level in the basics required for each course in the specialized
fields.
Doctoral program: The school admits those who have completed a master's program and want to work on
advanced research to acquire a doctorate degree, or working adults who aim to further improve their researchability to acquire a doctorate degree. Specifically, they should be those who have completed a master’s programin Japan and elsewhere who wish to obtain a doctoral degree in the information science field or working adults
who aim to obtain a doctoral degree. The school actively admits international students and adult students fromvarious fields by introducing various entrance examination systems. For the entrance examination of thedoctoral program, a specialized examination is conducted in English or Japanese. The specialized examinationconsists of a written test (paper) and an oral test to determine whether the applicant’s basic skills in thespecialized field are sufficient to receive research guidance in each course.
d. Educational content and methods
The Graduate School of Information Science and Technology provides interdisciplinary collaborativeeducation in the fields of information science, social science, mathematics, electrical science, electronics,
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communications, system science, biology, life science, and medical science to train leaders contributing to thedevelopment of the international community. Its main features are as follows:◈ International collaborative informatics subjects: Realization of new educational programs comprised ofcourse subjects in interdisciplinary fields on the back of advanced international collaborative research andeducation with multiple overseas universities◈ International collaborative guidance programs: Realization of educational programs in which students canenroll, take courses and obtain a degree in English through international collaboration◈ Re-learning by working adults: Enhancement of educational programs based on proven admission systems
and curricula (including e-learning) for working adults◈ Ingenuity in a common curriculum: Realization of a common curriculum that allows students to acquire
global perspectives, practical skills and interdisciplinary knowledge by creating international collaborative
informatics

subjects aimed at interdisciplinary collaborative education in cooperation with faculty

members from overseas universities, practical subjects aimed at skills to implement projects, and integrated
subjects in the humanities and sciences aimed at the acquisition of extensive knowledge of informationrelated laws and ethics. This is in addition to specialized subjects aimed at the acquisition of specialized
knowledge and skills related to information science◈ Adaptive research guidance system: Realization of a supervisor and co-supervisor system using faculty
members of multiple departments by establishing an education system through faculty member collaboration
centered on the Faculty of Information Science and Technology to respond to the needs of the times and thewishes of students
The graduate school offers students an option for flexibly taking various subjects. This makes it possible toprovide the latest education in advanced research fields.
The graduate school provides a curriculum that can be completed in English through international
collaborative informatics subjects with overseas partner universities and English subjects offered by each course.
Through these English lectures and international collaborative guidance programs with faculty members ofoverseas universities, the school aims to develop students with global perspectives.
E-learning (remote education system) is utilized to improve the re-learning of working adults and support
international collaborative informatics subjects. In addition to collaborative educational programs with othergraduate schools, research institutes and centers within the University, as well as overseas partner universities,
the graduate school also introduces unique educational programs such as joint educational programs andinternships with governmental research institutions and affiliated companies.
To contribute to the development of an advanced information society and promote a global knowledge-basedsociety under the four basic philosophies of the University (Frontier Spirit, Global Perspectives, All-round
Education and Practical Learning), through the succession and creation of information science theory the
Graduate School of Information Science and Technology cultivates engineers with extensive, profound
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academic knowledge and global perspectives and creative researchers who can independently conduct researchand development. With information science as the core, the graduate school creates new research areas from thefusion of various fields and develop individuals who can work globally.
The master's program cultivates innovation leaders (IL) who have advanced knowledge in the basic andspecialized fields of information science and excellent research and development capabilities based on practicalexperience and the creation of new knowledge, and who can play an active role in the international community.
The doctoral program cultivates frontier leaders (FL) who can create new research areas from the fusion ofvarious fields, acquire world-class research and development capabilities in specialized fields, and advanceresearch and development in a sophisticated knowledge-based society on the back of international collaboration.
To cultivate the above professionals, the graduate school’s students acquire the following knowledge andcapabilities:◈ Extensive basic knowledge in various relevant fields centered on information science◈ Practical knowledge that meets the needs of the global community◈ A high level of expertise to study information science and its boundary areas◈ World-class research capabilities based on advanced expertise
The basic concept for the formation and implementation of curriculums in the master's and doctoral programsof the new graduate school to cultivate the above-mentioned innovation and frontier leaders is as follows:
Master's program: A multi-field curriculum is implemented in which students take subjects provided in their
specialized course and other courses. Students can also take common subjects (international collaborative
informatics subjects, practical subjects and integrated subjects in the humanities and sciences), thereby
acquiring extensive basic knowledge, a high level of expertise, global perspectives and an ability to take action,
as well as gaining knowledge in border areas and different fields. The quality of education is assured throughcareful and substantial support for students, including career development, under the supervisor and cosupervisor system. The grade evaluation criteria are disclosed.
Doctoral program: The multi-field curriculum in the master’s program is expanded to require students to takesubjects in other fields than those they have learned in the master’s program.

Global perspectives aredeveloped through international collaborative guidance programs. The quality of education is assured throughcareful and substantial support for students, including career development, under the collaborative education
guidance committee system run by a supervisor and multiple co-supervisors. With this, students obtain thehighest level of expertise in the world. The grade evaluation criteria are disclosed.
The new graduate school consists of five courses, each of which offers specialized subjects. The core
specialized subjects of individual courses correspond to the following specialized areas:
1. Course of Computer Science and Information Technology: A specialized area related to computer science53

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and information systems, including information and mathematics subjects taught by members involved inmathematics at the Faculty of Science, and big data science subjects by GSB faculty members
2. Course of Electronics for Informatics: A specialized area related to information processing system hardwareand next-generation electronics
3. Course of Bioengineering and Bioinformatics: A specialized area related to science and technology
connected to life, humans and medicine
4. Course of Media and Network Technologies: A specialized area related to information media andinformation communication networks dealing with images, videos, audio, music and natural language,
including subjects related to complex systems and networks by GSB faculty
5. Course of Systems Science and Informatics: A specialized area related to electrical science, electronics,
management, information science, mechanical and system science
In the doctoral program, a doctoral degree in information science or a doctoral degree in engineering isawarded depending on the research content. A doctoral degree in information science is awarded for research
themes in the field of information science, such as “Scenario Verification for the Proximity-Based Federationof Smart Objects Using Model Checking” and “Study on Optical Information Processing by Virtual Phase
Conjugation Technique using Complex Amplitude Control,” while a doctoral degree in engineering is awarded
for research themes in the field of engineering, such as “Study on Mode Control of Random Lasers” and “Studyon the Application of Model Order Reduction to Electromagnetic Field Analysis” (these research themes arefrom titles of dissertations in FY 2017).
e. Outcomes of education
To implement the international education system at the new Graduate School of Information Science andTechnology ahead of schedule, the GSB has hired students, mainly doctoral students of the previous Graduate
School of Information Science and Technology, as research assistants, and provided opportunities to makepresentations at international symposiums attended by researchers with cross-appointments and otherinternationally renowned researchers.
Table 1 shows the numbers of research assistants hired by the GSB for every half year. In hiring research
assistants, the GSB introduced a system in which students are evaluated based on their research activities,
including article publication and prize-winning, and their contribution to GSB activities, and in which theevaluation is reflected to their hourly wage to improve research assistants’ motivation for research.
Table 1: Numbers of research assistants hired
The figure in parentheses shows the number of well-evaluated research assistants.
2016

2017

2018

2019

First half-

21 (8)

28 (13)22 (11)

Latter half

14 (5)

22 (9)

23 (9)

17 (9)

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In addition, the GSB provided research assistants with opportunities to present their research to overseas
researchers, including researchers from different fields, at international symposiums. Table 2 shows the numbersof research assistants who participated in international symposiums.
Table 2: Numbers of presentations by research assistants at international symposiums
The figure in parentheses shows the number of students other than research assistants (included number).
2017

2018

2019

Summer13 (3)

16

17

Winter-11

13 (4)

Three doctoral students of these research assistants were dispatched to UMass Amherst. Some of thesestudents presented a refereed paper co-authored with faculty members at the host university at an international
conference.
A total of 52 students served as research assistants, of whom 24 students have already graduated with a degree.
3. Establishment of Framework
3.1 Operating and administrative structure
Hokkaido University established the Global Institution for Collaborative Research and Education (GI-CoRE)
as a faculty organization under the direct control of the President that brings together world-class teaching staff
from around the world and within the University. It aims to promote international collaborative research andeducation that leverages the University’s strengths and distinctive features, and to provide support forinternational collaborative research and education being furthered independently by faculties or schools.
GI-CoRE was launched with three stations which are Global Stations for Quantum Medical Science andEngineering (GSQ) and Zoonosis Control (GSZ) in 2014, Food, Land and Water Resources (GSF) in 2015.
In April 2016, three new stations which are Big Data and Cybersecurity (GSB), Soft Matter (GSS), and Arctic
Research (GSA) were established. At present, since GSQ, GSZ, GSF closed their project successfully and the
new Global Station for Biosurfaces and Drug Discovery (GSD) was established in March 2020, there are fourglobal stations in GI-CoRE. GI-CoRE introduces new personnel and salary systems for its member researchers,
and it is positioned as a new education and research organization. President, who also serves as Director of GICoRE, will chair a steering committee and sets specific arrangements and packages for GI-CoRE members.
Under the GI-CoRE concept, the GSB was established to collaborate with the College of Information andComputer Sciences (CICS) of UMass Amherst, a research group involved in big data science and data security
initially. At the same time, research on the realization of a medical big data system, relevant clinicalbioinformatics, and medical informatics started in collaboration with Hokkaido University Hospital. Against
the backdrop of these collaborative studies, the GSB has established a structure for conducting intensive lectures,
including the development of collaborative educational programs with UMass CICS. Based on these activities,

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Under its Director, the GSB promotes research and education through organization-to-organization cooperation
with overseas universities, rather than conventional international exchange centered on the activities ofindividual researchers.
In FY 2017, in order to further promote globalization, the GSB started collaboration with the University ofTechnology, Sydney (UTS, Australia), which is a world-leading university in IoT technology, and built aninternational collaborative research group on IoT and cybersecurity. In addition to hosting international
symposiums each year, the GSB co-sponsors international conferences with other global stations or IEEE andother international academic societies, and introduces its activities related to international collaborative researchand education and improves its presence in various arenas, such as introducing GSB at domestic and overseas
events, and offering public lectures for the general public. The GSB also constructs new educational programs
centered on overseas researchers with cross-appointments and cooperates with the Summer Institute Program,building a track record suitable for a research and education hub. In order to carry out these various projects
promptly and efficiently, the GSB holds a regular project promotion meeting (meeting by the director, vicedirector and all members of the GSB secretariat, about once a month) and a steering committee meeting (meetingby all GSB faculty members in the University, about once every six months), as well as regular videoconferences with overseas faculty members to discuss all important matters related to GSB operations. In thisway, activities are smoothly promoted under the faculty-led operating structure.
To establish the Faculty of Information Science and Technology and the new Graduate School of Information
Science and Technology, which started in FY 2019, a graduate school preparatory committee that includes core
GSB members in Hokkaido University was set up in the previous Graduate School of Information Science andTechnology in FY 2018. An application for establishment was made to the Evaluation Committee for theChartering of Universities in March 2018 and approved in July 2018. With the reorganization into the Facultyof Information Sciences and Technology and the new Graduate School of Information Science and Technology
in FY 2019, a system with one division and multiple courses was established and a new human resource
development program was created at the new graduate school. Many of the HU members at the GSB belonged
to the previous Graduate School of Information Science. The new graduate school introduced international
collaborative informatics subjects and co-supervision by overseas faculty members with cross-appointments
based on the achievements of GSB's international collaborative research. Through these activities, a discussionof the introduction of a cotutelle program has been started.
In FY 2020, the GSB aims to further revitalize international collaborative research, activate the overseas
dispatch of students who belong to the Graduate School of Information Science and Technology, and obtaincompetitive research funds for research themes conducted by international collaborative research groups,
thereby expanding this project.

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3.2 Hosting structure, environment improvement and future vision
Education and research support structures:
Utilizing the framework of GI-CoRE led by the President, the GSB invites researchers from overseas topclass universities and research institutes and works with faculty members in relevant fields in the University topromote international collaborative research and education.
The GSB utilizes the cross-appointment system for overseas and HU faculty members as follows:
1. Overseas faculty members
The cross-appointment system with other institutes allows the University to hire researchers from research
institutes in Japan and elsewhere and to pay salaries according to their efforts while they remain employeesof their home institute. Such researchers are also exempt from administrative operations such as faculty
meetings and entrance examinations to secure an environment where they can concentrate on researcheducation. This has led to the invitation of top-class researchers from overseas, who could not normally be
invited. It has also led to the strategic acquisition of competitive research funds, such as KAKENHI, by young
overseas researchers with cross-appointments through collaboration with GSB members in the University.
2. HU faculty members
The system for appointment to GI-CoRE has also been used for researchers in the University, which promotesinternational collaborative research and education. This has helped to create opportunities for young
researchers with cross-appointments to participate in international collaborative research centered on thethemes handled by the GSB. As a result, such researchers have submitted and published many international
journal articles and international conference papers.
In addition to institutional aspects, the GSB provides young researchers with an appropriate research
environment and educational experience. The departments involved in this project have diversified, which has
led the advancement of interdisciplinary collaboration with the Department of Mathematics at the Faculty of
Science. These virtuous circles have since spread to relevant departments, and the functions of the University
have been further strengthened.
The vision of the GSB for the future is to further deepen, expand and practically operate the following two
points that have been pursued since the establishment.
1. Establishment of an international collaborative research hub in the field of information science related to
big data science, cybersecurity and IoT system construction, and the launch of international-level researchthrough collaboration between universities worldwide
2. Development of international higher education in relevant fields based on the above developments
The research areas of big data science, cybersecurity and IoT are not independent themes. They are closely
integrated with each other to advance research and development. Anticipated basic problems and appliedresearch have become more complicated. Accordingly, it is necessary to substantiate global organizational
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collaboration and promote it efficiently. The total number of research and development workers in these areas
is very small. There is a need for education programs that systematically provide new knowledge, and it isessential to enhance international higher education programs. The future vision is to deepen, expand andsubstantiate research and education in these areas.
Furthermore, while maximizing the collaborative research/education networks between the organizations andthe research results obtained so far, the GSB will further strengthen the research and education in which the
University excels, and practice "global graduate education that organically integrates different fields" in relevant
graduate schools. With regard to activity funds, in addition to subsides for operational expenses from thenational government, the GSB aims to obtain various types of funds, such as KAKENHI and other competitive
funds, as well as donations.
Global Station’s administrative structure:
In order to support the research and education activities at the GSB, it is necessary to strengthen the capabilityof the administrative section to deal with international affairs. The Global Station Office has bilingual staff
members to support international researchers’ daily research and education activities. Furthermore, the central
administrative section of GI-CoRE also has staff with experience in overseas study to provide support in English
for office procedures.
For many researchers with cross-appointments, it is very difficult to individually carry out various tasks
involved in their stay at Hokkaido University. Accordingly, such administrative support helps to make relatively
smooth invitations. In the future, remote guidance is expected to increase, but such support is indispensable
when actually inviting overseas researchers.

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Appendix: Research Achievements and List of Publications
2. Other Publications
2-2. Other Publications: Featured in International Conference Proceedings: #258
2021-20201)

Kentaro Kanamori, Takuya Takagi, Ken Kobayashi, Hiroki Arimura, “DACE: Distribution-Aware
Counterfactual Explanation by Mixed-Integer Linear Optimization”, Proc. the 29th International Joint
Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence(IJCAI-PRICAI 2020), January 2021. [Proc] †2)

J. Takano, T. Fujisawa, Y. Sawada, and K. Saitoh, “Low-loss silicon 2×4λ multiplexers composed of on-chippolarization-splitter-rotator and 2×2 and 2×1 Mach-Zehnder filters for 400GbE”, Optical Fiber Communication
Conference (OFC), Paper M3F.4, San Diego, USA, Mar. 8-12, 2020. [Proc] †3)

T. Fujisawa, T. Sakamoto, M. Miyata, T. Matsui, T. Hashimoto, R. Kasahara, K. Nakajima, and K. Saitoh,“Wavefront-matching-method-designed six-mode-exchanger based on grating-like waveguide on silica-PLC
platform”, Optical Fiber Communication Conference (OFC), Paper Th1A.5, San Diego, USA, Mar. 8-12, 2020.
[Proc] †4)

K. Nakamura, T. Fujisawa, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh, “A tunable mode divider basedon wavelength insensitive coupler using thermo-optic effect for gain-equalization in MDM network”, OpticalFiber Communication Conference (OFC), Paper Th2A.6, San Diego, USA, Mar. 8-12, 2020. [Proc] †5)

Y. Sawada, T. Fujisawa, and K. Saitoh, “Experimental Demonstration of Broadband Silicon Mode Converter
Designed by Wavefront-Matching Method”, Conference on Lasers and Electro-Optics (CLEO), Paper SM4J.6,
San Jose, USA, May 10-15, 2020. [Proc] †6)

Y. Sawada, T. Fujisawa, and K. Saitoh, “Broadband Design of Silicon Photonics Four-Mode (de)Multiplexer by
Wavefront Matching Method”, Advanced Photonics Congress (APC), Paper ITh3A.6, Virtual Conference, July
13-16, 2020. [Proc] †7)

K. Saitoh, T. Fujisawa, and T. Sato, “Control of Group Delay Spread in Randomly-Coupled Multicore Fibers”,
Optoelectronics and Communications Conference (OECC), Paper T3-1, Taipei, Taiwan, Oct 4-8, 2020. [Proc] †8)

Y. Wang, T. Fujisawa, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh, “Step index 8-core fiber with 125um cladding diameter for O-band use”, Optoelectronics and Communications Conference (OECC), Paper T32.4, Taipei, Taiwan, Oct. 4-8, 2020. [Proc] †9)

T. Fujisawa and K. Saitoh, “Ultrasmall two-mode dividers based on mosaic structure designed by direct-binarysearch algorithm aided by artificial neural network”, Optoelectronics and Communications Conference (OECC),
Paper T5-1.3, Taipei, Taiwan, Oct. 4-8, 2020. [Proc] †116

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10) N. Sugawara, T. Fujisawa, K. Nakamura, Y. Sawada, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh,“Mode Amplitude and Phase Estimation using Multimode NFP by ANN”, Optoelectronics and Communications
Conference (OECC), Paper T5-2.5, Taipei, Taiwan, Oct. 4-8, 2020. [Proc] †11) K. Saitoh, “Few-mode Multi-core Fibres: Weakly-coupling and Randomly-coupling”, European Conference on
Optical Communications (ECOC), Paper Tu4A-1, Virtual Conference, Dec. 6-10, 2020. [Proc] †12) N. Sugawara, T. Fujisawa, N. Nakamura, Y. Sawada, T. Sakamoto, T. Matsui, K. Nakajima, and K. Saitoh,“Modal Amplitude and Phase Estimation of NFP of Six-Mode FMF Based on Artificial Neural Network with
the Help of Grey-Wolf-Optimizer”, European Conference on Optical Communication (ECOC), Paper Tu2A-6,
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Mixed and Augmented Reality (ISMAR 2020) (2020) [Proc] †14) Takuya Inoue, Toshikazu Teshigawara, Yusuke Yamauchi, Sakae Taniguchi, Takahisa Ono, Hiroshi Hamada,
Hiroyuki Miyoshi, Fumito Minoura Tomoki Kitashima, Masahito Hashimoto, Masashi Iwaki, Yuka Saito,
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Conference on Image Processing (ICIP 2020), pp.1236-1240 (2020) [Proc] †19) Saya Takada, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Estimation of visual contents based on question
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pp.61-65 (2020) [Proc] †20) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: "Feature integration via geometricalsupervised multi-view multi-label canonical correlation for incomplete label assignment", 2020 IEEE
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learning using acoustic feature map", 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE 2020),
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Electronics (GCCE 2020), pp.667-669 (2020) [Proc] †28) Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Important scene prediction of baseball
videos using twitter and video analysis based on LSTM", 2020 IEEE 9th Global Conference on Consumer
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on matrix completion”2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019), pp.233234(2019)108) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Estimation of emotion labels via tensorbased spatiotemporal visual attention analysis”2019 IEEE International Conference on Image Processing(ICIP 2019), pp.4105-4109(2019)109) Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Scene retrieval for video summarization
based on text-to-image GAN”2019 IEEE International Conference on Image Processing (ICIP 2019),
pp.1825-1829(2019)110) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Neural network maximizing ordinallysupervised multi-view canonical correlation for deterioration level estimation”2019 IEEE International
Conference on Image Processing (ICIP 2019), pp.919-923(2019)111) Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Gastritis detection from gastric x-ray images
via fine-tuning of patch-based deep convolutional neural network”2019 IEEE International Conference on
Image Processing (ICIP 2019), pp.1371-1375(2019)112) Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Synthetic image generation for gastritis
detection based on auxiliary classifier generative adversarial network”IEEE International Symposium on
Circuits and Systems (ISCAS 2019)(2019)113) Zongyao Li, Ren Togo, Takahiro Ogawa and Miki Haseyama: “Semi-supervised Learning Based on Tritraining for Gastritis Classification Using Gastric X-ray Images”2019 IEEE International Symposium on
Circuits and Systems (ISCAS)(2019)114) Rintaro Yanagi, Ren Togo, Takahiro Ogawa and Miki Haseyama: “Scene Retrieval from Multiple
Resolution Generated Images Based on Text-to-image GAN”2019 IEEE International Symposium on
Circuits and Systems (ISCAS2019)(2019)115) Yui Matsumoto, Shota Hamano, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Bilingual Lexicon
Learning Using Tagged Images via Graph Trilateral Filter-based Feature Refinement”2019 IEEE
International Conference on Consumer Electronics - Taiwan (ICCE-TW), pp.729-730(2019)116) Masanao Matsumoto, Naoki Saito, Takahiro Ogawa, Miki Haseyama: “Convolutional Sparse Codingbased Anomalous Event Detection in Surveillance Videos”2019 IEEE International Conference on
Consumer Electronics - Taiwan (ICCE-TW), pp.483—484(2019)117) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “User-Specific Visual Attention
Estimation Based on Visual Similarity and Spatial Information in Images”2019 IEEE International
Conference on Consumer Electronics - Taiwan (ICCE-TW), pp.479-480(2019)118) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa and Miki Haseyama: “Multi-feature Fusion Based on
Supervised Multi-view Multi-label Canonical Correlation Projection”2019 IEEE International Conferenceon Acoustics, Speech and Signal Processing (ICASSP), pp.3936-3940(2019)119) Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa and Miki Haseyama: “Estimating Viewed Image
Categories from Human Brain Activity via Semi-supervised Fuzzy Discriminative Canonical Correlation
Analysis”2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),

126

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pp.1105-1109(2019)120) Ren Togo, Takahiro Ogawa, Osamu Manabe, Kenji Hirata, Tohru Shiga and Miki Haseyama: “Extractionof regions related to cardiac sarcoidosis in polar map images”, 2019 IEEE 1st Global Conrefence on Life
Sciences and Technologies (LifeTech 2019), pp.237-238 (2019) *ii)
121) Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Estimation of users' interest levels
using tensor completion with SemiCCA”, 2019 IEEE 1st Global Conference on Life Sciences andTechnologies (LifeTech2019), pp.239-340 (2019)122) Haruna Watanabe, Ren Togo, Takahiro Ogawa and Miki Haseyama: “Bone Metastatic Tumor Detection
Based on AnoGAN Using CT Images”, IEEE Global Conference on Life Sciences and Technologies(LifeTech 2019), pp.235-236 (2019)123) Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa and Miki Haseyama: “Semi-supervised
Discriminative CCA for Estimating Viewed Image Categories from fMRI Data”, 2019 IEEE 1st Global
Conference on Life Sciences and Technologies (LifeTech 2019), pp.233-234 (2019)124) Masanao Matsumoto, Naoki Saito, Takahiro Ogawa, Miki Haseyama: “Chronic Gastritis Detection from
Gastric X-ray Images via Deep Autoencoding Gaussian Mixture Models”, 2019 IEEE 1st Global
Conference on Life Sciences and Technologies (LifeTech2019), pp.231,232 (2019)125) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “Estimation of Visual Attention via
Canonical Correlation between Visual and Gaze-based Features”, 2019 IEEE 1st Global Conference onLife Sciences and Technologies (LifeTech 2019), pp.229-230 (2019)126) Akira Toyoda, Takahiro Ogawa, Miki Haseyama: “Video Classification Based on User Preferences with
Soft-bag Multiple Instance Learning”, IEEE Global Conference on Life Sciences and Technologies(LifeTech2019), pp.198-199 (2019)
127) Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Fine-tuning of pre-trained dcnn for gastritis
detection from gastric x-ray images”, 2019 IEEE 1st Global Conference on Life Sciences and Technologies(LifeTech 2019), pp.196-197 (2019)128) Taiga Matsui, Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, and Miki Haseyama: “Estimation of
Emotions Evoked by Images Based on Multiple Gaze-based CNN Features”, IEEE Global Conference onLife Sciences and Technologies (LifeTech2019), pp.194-195 (2019)129) Zongyao Li, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Classification of subcellular protein patterns
in human cells with transfer learning”, 2019 IEEE 1st Global Conference on Life Sciences andTechnologies (LifeTech2019), pp.273-274 (2019)130) Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Field Position Estimation in Soccer
Videos Using Convolutional Neural Network-based Image Features”, The 2019 joint International
Workshop on Advanced Image Technology & International Forum on Medical Imaging in Asia,
pp.110490Y (2019)131) Taiga Matsui, Naoki Saito, Takahiro Ogawa, Satoshi Asamizu and Miki Haseyama: “Gaze-based Visual
Feature Extraction via DLPCCA for Visual Sentiment Estimation”, The 2019 joint International Workshop
on Advanced Image Technology & International Forum on Medical Imaging in Asia, pp.110490Q (2019)127

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132) Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama: “Classification of Tourism Categories
Based on Heterogeneous Features Considering Existence of Reliable Results”, The 2019 joint International
Workshop on Advanced Image Technology & International Forum on Medical Imaging in Asia,
pp.1104905 (2019)133) Haruna Watanabe, Ren Togo, Takahiro Ogawa, Miki Haseyama, Koichi Yasuda, Khin Khin Tha, Kohsuke
Kudo, Hiroki Shirato: “Automatic Metastatic Bone Tumor Classification with DCNN-based Features
Using Treatment-planning CT Images”, The 2019 joint International Workshop on Advanced Image
Technology & International Forum on Medical Imaging in Asia, pp.110501A (2019)134) Masaharu Yoshioka, and Shinjiro Hara, “Construction of an In-House Paper/Figure Database System Using
Portable Document Format Files”. In Information Search, Integration, and Personalization: 10th
International Workshop, ISIP 2018, Dimitris Kotzinos, Dominique Laurent, Nicolas Spyratos, Yuzuru
Tanaka, and Rin-ichiro Taniguchi (eds), pp. 142-156, Springer-Verlag GmbH, CCIS 1040, 2019. [OV][Proc]*i)135) Masaharu Yoshioka and Zihao Song, “HUKB at COLIEE 2019 Information Retrieval Task - Utilization of
metadata for relevant case retrieval – “, In Proceedigns of the Sixth International Competition on Legal
Information Extraction/Entailment (COLIEE 2019), pp. 33-37, 2019. [OV] [Proc]*i)136) A. Yamamoto, T. Nishimura, T. Ohgane, T. Tandai, D. Uchida, “Evaluation of OAM Mode Multiplexing
Considering Ground Reflection,” IEEE International Conference on Communications (IEEE ICC 2019),
Shanghai, China, May. 2019. [OV] [Proc]
137) S. Nakamura, T. Nishimura, T. Ohgane, Y. Ogawa, J. Hagiwara, “Loose Beamforming by Antenna
Selection in a Multiuser Massive MIMO System,” IEEE Asia Pacific Wireless Communications
Symposium (IEEE APWCS 2019), SUTD, Singapore, Aug. 2019. [OV] [Proc]
138) Kanako Yamaguchi, Masatsugi Higashinaka, Hiroyasu Sano, Atsushi Okamura, Mitsubishi Electric
Corporation; Takeo Ohgane, “A Narrow-band Coherent FSK Transmission System Using Phase RotatedTransmit Diversity with Suppression of Envelope Fluctuation”, Vehicular Technology Conference(VTC2019), HONOLULU, HAWAII, Sep. 2019 [OV] [Proc]
139) R. Li, Y. Ogawa, T. Nishimura, T. Ohgane, J. Hagiwara, “A Study on Performance Improvement by CRCAided GaBP for Large-Scale SCMA Detection,” Wireless Personal Multimedia Communications (WPMC
2019), LISBOA, PORTUGAL, Nov. 2019. [OV] [Proc]
140) Y. Kase, T. Nishimura, T. Ohgane, Y. Ogawa, D. Kitayama, Y. Kishiyama, “Performance Analysis of DOA
Estimation of Two Targets Using Deep Learning,” Wireless Personal Multimedia Communications(WPMC 2019), LISBOA, PORTUGAL, Nov. 2019. [OV][Proc]
141) W. Kawabata, T. Nishimura, T. Ohgane, Y. Ogawa, “A Study on Large-Scale Signal Detection Using
Gaussian Belief Propagation in Overloaded Interleave Division Multiple Access,” Wireless Personal
Multimedia Communications (WPMC 2019), LISBOA, PORTUGAL, Nov. 2019. [OV] [Proc]
142) K. Fukuda, T. Nishimura, T. Ohgane, Y. Ogawa, “A Study on Iterative Equalization with GaBP and Soft
Successive Cancellation List Decoding in a Polar-Coded System,” Wireless Personal Multimedia
Communications (WPMC 2019), LISBOA, PORTUGAL, Nov. 2019. [OV] [Proc]

128

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143) K. Saito, Y. Ogawa, T. Nishimura, T. Ohgane, J. Hagiwara, “Computational Complexity Reduction of
Receive Weight Matrices in Massive MIMO SC-FDE,” International Conference on Computing,
Networking and Communications (ICNC 2019), Honolulu, Hawaii, Feb. 2019. [OV] [Proc]
144) Y. Suzuki, T. Nishimura, T. Ohgane, Y. Ogawa, J. Hagiwara, “A Study on Layouts of Distributed Antenna
Arrays in an Indoor Multi-User Massive MIMO System,” International Conference on Computing,
Networking and Communications (ICNC 2019), Honolulu, Hawaii, Feb. 2019. [OV] [Proc]
145) Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto, “Modeling place and head-direction cells selforganized in different environments using recurrent neural networks”, 24th International Symposium on
Artificial Life and Robotics (AROB 24th 2019), 2019 [JP, International Symposium] [Proc] *ii)
146) Naohiro Shibuya, Hiroyuki Iizuka and Masahito Yamamoto, “Group Decision Making through Behavioral
Interaction in Robot Swarm”, 2019 IEEE/SICE International Symposium on System Integration (SII2019),
764 – 769, 2019 [OV][Proc]
147) Ryota Sekiya, Satoshi Oyama and Masahito Kurihara, “User-adaptive preparation of mathematical puzzles
using item response theory and deep learning”, Proceedings of the 32nd International Conference on
Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2019), pp. 530-537,
2019. [OV][Proc]
148) Kyohei Atarashi, Akimi Moriyama, Satoshi Oyama and Masahito Kurihara, “A personalized affectresponse model for online news articles”, Proceedings of the Fifth Linguistic and Cognitive Approaches
To Dialog Agents Workshop (LaCATODA 2019), 2019. [OV][Proc]*ii)
149) Shoma Kikuchi, Ichigaku Takigawa, Satoshi Oyama, and MasahitoKurihara, “Learning relevant molecular
representations via self-attentive graph neural networks”, Proceedings of the Workshop on Deep Graph
Learning: Methodologies and Applications (DGLMA 2019), pp.5364-5369, 2019. [OV][Proc]*ii)
150) Jing Song, Satoshi Oyama, and Masahito Kurihara, “Identification of Possible Common Causes by Intrinsic
Dimension Estimation”, In Proceedings of the 2019 IEEE International Conference on Big Data and Smart
Computing (IEEE BigComp 2019), February 2019. [OV][Proc]
151) Tomoumi Takase, Satoshi Oyama and Masahito Kurihara, “Evaluation of Stratified Validation in Neural
Network Training with Imbalanced Data”, In Proceedings of the 2019 IEEE International Conference on
Big Data and Smart Computing (IEEE BigComp 2019), February 2019. [OV] [Proc]*i) ii)
2018152) Yoshikazu Miyanaga, Hiroshi Tsutsui, Junji Yamano, Masaki Miura, Tohru Gotoh, Takashi Imagawa,“Development of Real-time FHD Loss-Less Video Communication over an 8×8 MIMO-OFDM System,”
Proceedings of Asia-Pacific Signal and Information Processing Association Annual Summit andConference (APSIPA ASC), Nov. 2018.
153) Yoshikazu Miyanaga, Hiroshi Tsutsui, Junji Yamano, Masaki Miura, Tohru Gotoh, Takashi Imagawa,“Development of High Performance RF Modules Used in Real-time FHD Video Communication over 8x8
MIMO-OFDM System,” Proceedings of International Symposium on Intelligent Signal Processing andCommunication Systems (ISPACS), Nov. 2018.
154) Jiayue Tang, Yu Tian, Xiaonan Jiang, Hiroshi Tsutsui, Yoshikazu Miyanaga, “An Evaluation of Keyword

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Detection Using ACF of Pitch for Robust Speech Recognition,” Proceedings of International Symposiumon Communications and Information Technologies (ISCIT), pp. 96-100, Sep. 2018.
155) Yu Tian, Jiayue Tang, Xiaonan Jiang, Hiroshi Tsutsui, Yoshikazu Miyanaga, “Accuracy on Children's
Speech Recognition under Noisy Circumstances,” Proceedings of International Symposium on
Communications and Information Technologies (ISCIT), pp. 101-104, Sep. 2018.
156) Yu Tian, Jiayue Tang, Xiaonan Jiang, Hiroshi Tsutsui, Yoshikazu Miyanaga, “Robust Children Isolated
Speech Recognition System Using RSA and RSF,” Proceedings of International Symposium on Multimedia
and Communication Technology (ISMAC), pp. 113-116, Aug. 2018.
157) Jiayue Tang, Yu Tian, Xiaonan Jiang, Hiroshi Tsutsui, Yoshikazu Miyanaga, “Keyword Detection Using
F0-VAD in Robust Isolated Phase Recognition System,” Proceedings of International Symposium on
Multimedia and Communication Technology (ISMAC), pp. 121-124, Aug. 2018.
158) Yunako Katagishi, So Tsuyuguchi, Hiroshi Tsutsui, Yoshikazu Miyanaga, “An Evaluation of Entropy
Coding Approaches in Block-Based Adaptive Lossless Image Coding Method for Embedded Systems,”
Proceedings of International Symposium on Multimedia and Communication Technology (ISMAC), Aug.
2018.
159) Kazuhiro Kurita, Kunihiro Wasa, Hiroki Arimura, Takeaki Uno, “Efficient Enumeration of Dominating
Sets for Sparse Graphs”, Proceedings of the 29th International Symposium on Algorithms and Computation(ISAAC 2018). (Hotel Royal Chiaohsi, Jiaoxi, Yilan County, Taiwan, December 16-19, 2018) [OV] [Proc]
160) Kazuhiro Kurita, Kunihiro Wasa, Alessio Conte, Takeaki Uno, and Hiroki Arimura, “Efficient Enumerationof Subgraphs and Induced Subgraphs with Bounded Girth”, Proceedings of the 29th International
Workshop (IWOCA 2018) on Combinatorial Algorithms, Lecture Notes in Computer Science, Springer,
vol.10979, pp.201-213, 2018. (IWOCA 2018, School of Computing, National University of Singapore(NUS), Singapore, 16-19 July 2018) [OV] [Proc]
161) Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Estimation of Important Scenes in
Soccer Videos Based on Collaborative Use of Audio-Visual CNN Features”, 2018 IEEE 7th Global
Conference on Consumer Electronics (GCCE 2018), pp.675-676 (2018)162) Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Team Tactics Estimation in Soccer
Videos via Deep Extreme Learning Machine Based on Players Formation”, 2018 IEEE 7th Global
Conference on Consumer Electronics (GCCE2018), pp.85-86 (2018)163) Shoji Takimura, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Twitter Followee
Recommendation Based on Multimodal FFM Considering Social Relations”, 2018 IEEE 7th Global
Conference on Consumer Electronics (GCCE 2018), pp.173-174 (2018)164) Kazaha Horii, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “A Human-Centered Neural Network
Model with Discriminative Locality Preserving Canonical Correlation Analysis for Image Classification”,
25th IEEE International Conference on Image Processing (ICIP), pp.2366-2370 (2018)
165) Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa and Miki Haseyama: “Estimation of Viewed
Image Categories via CCA Using Human Brain Activity”, 2018 IEEE 7th Global Conference on Consumer
Electronics (GCCE 2018), pp.171-172 (2018)130

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166) Masanao Matsumoto, Naoki Saito, Takahiro Ogawa, Miki Haseyama: “Missing Image Data Estimation via
Iterative Convolutional Sparse Coding”, 2018 IEEE 7th Global Conference on Consumer Electronics(GCCE 2018), pp.169,170 (2018)167) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: “User-centric Visual Attention
Estimation Based on Relationship Between Image and Eye Gaze Data”, 2018 IEEE 7th Global Conference
on Consumer Electronics (GCCE 2018), pp.44-45 (2018)168) Rintaro Yanagi, Ren Togo, Takahiro Ogawa and Miki Haseyama: “Image Retrieval from Vague Description
Based on AttnGAN”, 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018), pp.167168 (2018)169) Ken Kawakami, Takahiro Ogawa, Miki Haseyama: “Blood Circulation Based on PPG Signals for Thermal
Comfort Evaluation”, 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018), pp.163164 (2018)170) Ken Kawakami, Takahiro Ogawa, Miki Haseyama: “Detection of Deformed PPG Waveforms Based on a
Ratio of Their Average Accelerations”, 2018 IEEE 7th Global Conference on Consumer Electronics(GCCE 2018), pp.165-166 (2018)171) Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “ANONYMOUS GASTRITIS IMAGE
GENERATION VIA ADVERSARIAL LEARNING FROM GASTRIC X-RAY IMAGES”, International
Conference on Image Processing (ICIP), pp.2082-2086 (2018)172) Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama: “Tourism Category Classification Basedon Novel Decision-making Process from Multiple Results”, GI-CoRE GSQ, GSB & IGM Joint Symposium(2018) *ii)
173) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Distress Classification via Neural
Network Maximizing Canonical Correlation between Multi-modal Features”, GI-CoRE GSQ, GSB & IGM
Joint Symposium (2018) *ii)174) Yui Matsumoto, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Simultaneous Realization ofMultiple Music Video Applications Based on Heterogeneous Network Analysis via Latent Link
Estimation”, IEEE International Conference on Multimedia and Expo (ICME2018), pp.1-6 (2018)175) Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Interest Level Estimation of Items
via Matrix Completion Based on Adaptive User Matrix Construction”, IEEE International Conference on
Multimedia and Expo (ICME2018), pp.1-6 (2018)176) Ren Togo, Kenji Hirata, Osamu Manabe, Hiroshi Ohira, Ichizo Tsujino, Takahiro Ogawa, Miki Haseyama,
Tohru Shiga: “Use of deep convolutional neural network-based features for detection of cardiac sarcoidosis
from polar map”, Society of Nuclear Medicine and Molecular Imaging Annual Meeting 2018 (SNMMI)(2018)
177) Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama: “Tourism Category Classification on
Image Sharing Services Through Estimation of Existence of Reliable Results”, ACM International
Conference on Multimedia Retrieval (ICMR2018), pp.493-496 (2018) *ii)
178) Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “ANONYMOUS IMAGE DATA

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GENERATION FROM GASTRIC X-RAY IMAGES FOR IMPROVING GASTRITIS RECOGNITIONPERFORMANCE”, IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW),
pp.181-182 (2018)179) Akira Toyoda, Takahiro Ogawa, Miki Haseyama: “Semi-supervised Multiple Feature Fusion for Video
Preference Estimation”, IEEE International Conference on Acoustics, Speech, and Signal Processing(ICASSP2018), pp.891-895 (2018)180) Yoshiki Ito, Takahiro Ogawa, Miki Haseyama: “SFEMCCA: Supervised Fractional-Order Embedding
Multiview Canonical Correlation AnalysisFor Video Preference Estimation”, IEEE International
Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp.3086-3090 (2018)181) Masaharu Yoshioka: Analysis of COLIEE Information Retrieval Task Data. In New Frontiers in Artificial
Intelligence. JSAI-isAI 2017. Lecture Notes in Computer Science, pp. 5-19, Springer International
Publishing, Cham, LNCS10838, 2018. [OV]182) Masaharu Yoshioka and Zihao Song: HUKB at COLIEE2018 Information Retrieval Task. In Proceedingsof the twelfth International Workshop on Juris-Informatics (JURISIN2018), pp. 183-193, The JapaneseSociety of Artificial Intelligence, 2018. [International Conference]
183) Masaharu Yoshioka, Yoshinobu Kano, Naoki Kiyota, and Ken Satoh: Overview of Japanese Statute Law
Retrieval and Entailment Task at COLIEE-2018. In Proceedings of the twelfth International Workshop on
Juris-Informatics (JURISIN2018), pp. 117-128, The Japanese Society of Artificial Intelligence, 2018.
[International Conference] *i)184) Masaharu Yoshioka: WC3: Wikipedia Category Comprehensiveness Checker based on the DBpedia
Metadata Database. In Workshop and Poster Proceedings of the 8th Joint International Semantic
Technology Conference co-located with the 8th Joint International Semantic Technology Conference (JIST2018), pp. 98-101, 2018. [OV]185) J. Yamamoto, T. Nishimura, T. Ohgane, Y. Ogawa, Y. Kishiyama, “Performance Evaluation on Beam
Shapes of a Large MIMO System,” 2018 IEEE International Workshop on Antenna Technology (iWAT),
Nanjing, China, Mar. 2018. [OV][Proc]
186) K. Inoue, T. Nishimura, T. Ohgane, Y. Ogawa, “A Basic Study on Antenna Selection for Loose
Beamforming in Massive MIMO System,” 2018 IEEE International Workshop on Antenna Technology(iWAT), Nanjing, China, Mar. 2018. [OV][Proc]
187) T. Hoshikawa, T. Nishimura, T. Ohgane, Y. Ogawa, J. Hagiwara, “Performance Comparison of Compressed
Sensing Algorithms for DOA estimation of Multi-band Signals,” 2018 IEEE Workshop on Positioning,
Navigation and Communications (WPNC), Bremen, Germany, Oct. 2018. [OV][Proc]
188) Y. Kase, T. Nishimura, T. Ohgane, Y. Ogawa, D. Kitayama, Y. Kishiyama, “DOA Estimation of Two Targets
with Deep Learning,” 2018 IEEE Workshop on Positioning, Navigation and Communications (WPNC),
Bremen, Germany, Oct. 2018. [OV][Proc]
189) T. Watabe, T. Nishimura, T. Ohgane, Y. Ogawa, J. Hagiwara, “Superposed 16-QAM Signal Detection Using
GaBP in a Massive MIMO System,” Asia-Pacific Signal and Information Processing Association Annual
Summit and Conference 2018 (APSIPA ASC), Honolulu, Hawaii, Nov. 2018. [OV][Proc]

132

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190) Kenji Hirata, Hiroyuki Iizuka, Masahito Yamamoto, “Deep Reinforcement Learning Method Enabling
Stable Learning in Multi-Agent Environment”, The 22nd Asia Pacic Symposium on Intelligent and
Evolutionary Systems (IES2018), 163~168, 2018 [OV][Proc]
191) Hironobu Horiuchi, Hiroyuki Iizuka, Masahito Yamamoto, “Differentiation of communication signals toestablish cooperation using Deep Q-Network”, The 22nd Asia Pacic Symposium on Intelligent and
Evolutionary Systems (IES2018), 156~162, 2018 [OV][Proc]
192) Takafumi Suzuki, Satoshi Oyama, and Masahito Kurihara, “Toward Explainable Recommendations:
Generating Review Text from Multicriteria Evaluation Data”, In Proceedings of the Second IEEE
Workshop on Human-in-the-loop Methods and Human Machine Collaboration in BigData (IEEE HMData2018), pp. 3548-3550, December 2018. [OV][Proc]
193) Yuko Sakurai, Jun Kawahara, and Satoshi Oyama, “Aggregating Crowd Opinions Using Shapley Value
Regression”, In Proceedings of the 12th Multi-Disciplinary International Conference on Artificial
Intelligence (MIWAI 2018), November 2018. [OV][Proc]
194) Taiju Matsui, Satoshi Oyama, and Masahito Kurihara, “Effect of Viewing Directions on Deep
Reinforcement Learning in 3D Virtual Environment Minecraft”, In Proceedings of the 21st International
Conference on Principles and Practice of Multi-Agent Systems (PRIMA 2018), pp. 527-534, October 2018.
[OV][Proc] *i)195) Hiroyuki Ihara, Shunsuke Imai, Satoshi Oyama, and Masahito Kurihara, “Implementation and Evaluationof Information Set Monte Carlo Tree Search for Pokémon”, In Proceedings of the 2018 IEEE International
Conference on Systems, Man, and Cybernetics (IEEE SMC 2018), pp. 2178-2183, October 2018.
[OV][Proc] *i)196) Jing Song, Satoshi Oyama, and Masahito Kurihara, “A Framework for Crowd-based Causal Analysis ofOpen Data”, In Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics(IEEE SMC 2018), pp. 2184-2189, October 2018. [OV][Proc]
197) Tomoumi Takase, Satoshi Oyama, and Masahito Kurihara, “Longer Distance Weight Prediction for Faster
Training of Neural Networks”, In Proceedings of the 2018 IEEE International Conference on Systems,
Man, and Cybernetics (IEEE SMC 2018), pp. 2190-2195, October 2018. [OV][Proc] *i) ii)
198) Shinsaku Sakaue, Masakazu Ishihata, Shin-ichi Minato, “Eﬃcient Bandit Combinatorial Optimization
Algorithm with Zero-Suppressed Binary Decision Diagrams”, Proc. of the 21st International Conferenceon Articial Intelligence and Statistics (AISTATS 2018), April, 2018. [OV][Proc]
2017199) Iku Ohama, Issei Sato, Takuya Kida, Hiroki Arimura, “On the Model Shrinkage Effect of Gamma Process
Edge Partition Models”, Proc. the 31st Annual Conference on Neural Information Processing Systems(NIPS2017), December 2017 (to appear). (Also appeared as: arXiv:1709.08770, 26 Sep. 2017) [OV] [Proc]
200) Junpei Komiyama, Masakazu Ishihata, Hiroki Arimura, Takashi Nishibayashi, Shin-Ichi Minato,“Statistical Emerging Pattern Mining with Multiple Testing Correction”, In Proceedings of the 23rd ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2017), Research
Track, Hafifax, Nova Scotia, Canada, August 13-17, pp.897-906, 2017. DOI: 10.1145/3097983.3098137,

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[OV] [Proc]
201) Iku Ohama, Hiromi Iida, Takuya Kida, and Hiroki Arimura, “Discovering Relevance-Dependent Bicluster
Structure from Relational Data”, Proc. the 26th International Joint Conference on Artificial Intelligence(IJCAI 2017), Melbourne, pp.August 2017. DOI: 10.24963/ijcai.2017/359, [OV] [Proc]
202) Takuya Takagi, Keisuke Goto, Yuta Fujishige, Shunsuke Inenaga, Hiroki Arimura, “Linear-size CDAWG:
new repetition-aware indexing and grammar compression”, In Proceedings of the 24th International
Symposium on String Processing and Information Retrieval (SPIRE 2017), Lecture Notes in Computer
Science, Vol.10508, pp.304-316, September 2017. DOI: 10.1007/978-3-319-67428-5_26, (accepted for
publication; SPIRE 2017, 26th-29th September, 2017 - Palermo, Italy) (also appeared in: arXiv:1705.09779[cs.DS], [OV] [Proc]
203) Hiroki Arimura, Kazuhito Osabe, Takeaki Uno, “Optimization and Enumeration of Decision Trees from
Massive Data Sets”, Proc. 21st Conference of the International Federation of Operational ResearchSocieties (IFORS 2017), ME-18, Quebec, Canada, July 16-21, 2017. [OV] [Proc]
204) Hiroki Arimura, Kazuhito Osabe, Takeaki Uno, “Fast Enumeration Algorithms for Induced Trees in
Graphs”, Proc. 21st Conference of the International Federation of Operational Research Societies (IFORS2017), Quebec, Canada, July 16-21, 2017. [OV] [Proc]
205) Akira Toyoda, Takahiro Ogawa, Miki Haseyama: “Video Preference Estimation Using fNIRS Signals”,
IEEE Global Conference on Consumer Electronics (GCCE2017), pp.297-298 (2017)206) Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama: “Aesthetic Quality Assessment of Images via
Supervised Locality Preserving CCA”, IEEE Global Conference on Consumer Electronics (GCCE2017),
pp.258-259 (2017)
207) Tetsuya Kushima, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Interest Level Estimation Based on
Matrix Completion via Rank Minimization”, IEEE Global Conference on Consumer Electronics(GCCE2017), pp.299-300 (2017)208) Shoji Takimura, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Personalized Tweet
Recommendation Based on Field-aware Factorization Machines with Adaptive Field Organization”, IEEE
Global Conference on Consumer Electronics (GCCE2017), pp.260--261 (2017)209) Kazaha Horii, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Image Classification for Trend
Prediction Based on Integration of fNIRS and Visual Features”, IEEE Global Conference on Consumer
Electronics (GCCE2017), pp.301-302 (2017)210) Yui Matsumoto, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Construction of Network Using
Heterogeneous Social Metadata for Music Video Recommendation”, IEEE Global Conference on
Consumer Electronics (GCCE2017), pp.316-317 (2017)211) Yoshiki Ito, Takahiro Ogawa, Miki Haseyama: “Preference Estimation for Video Recommendation Using
DCNN Features and Viewing Behavior”, IEEE Global Conference on Consumer Electronics (GCCE2017),
pp.295-296 (2017)212) Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Detection of Gastric Cancer Risk from X-ray Images
via Patch-based Convolutional Neural Network”, IEEE International Conference on Image Processing

134

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(ICIP 2017), pp.2055-2059 (2017)213) Susumu Genma, Takahiro Ogawa, Miki Haseyama: “Image Retrieval Based on LRGA Algorithm andRelevance Feedback For Insect Identification”, IEEE International Conference on Image Processing (ICIP2017), pp.3978-3982 (2017)214) Shota Hamano, Takahiro Ogawa, Miki Haseyama: “Tag Refinement Based on Multilingual Tag Hierarchies
Extracted from Image Folksonomy”, IEEE International Conference on Image Processing (ICIP 2017),
pp.1327-1331 (2017)215) Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: “Automatic Martian Dust Storm Detection via Decision
Level Fusion Based on Deep Extreme Learning Machine”, IEEE International Conference on Image
Processing (ICIP 2017), pp.435-439 (2017)216) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Automatic Estimation of Deterioration
Level on Transmission Towers via Deep Extreme Learning Machine Based on Local Receptive Field”,
IEEE International Conference on Image Processing (ICIP 2017), pp.2379-2383 (2017)217) Akira Toyoda, Takahiro Ogawa, Miki Haseyama: “MvLFDA-based Video Preference Estimation Using
Complementary Properties of Features”, IEEE International Conference on Image Processing (ICIP 2017),
pp.635-639 (2017)218) Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Detection of Gastric Cancer Risk from X-ray Images
Based on Machine Learning”, GSB Workshop - Big-data Analysis, IoT and Bioinformatics, pp.7-8 (2017)*ii)219) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Deterioration Level Estimation on
Transmission Towers Based on Machine Learning”, GI-CoRE GSQ, GSB & IGM Joint Symposium, pp.56 (2017) *ii)220) Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Estimation of Regions Related to
Helicobacter Pylori Infection from Gastric X-ray Images”, GI-CoRE GSQ, GSB & IGM Joint Symposium,
pp.7-8 (2017) *ii)
221) Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Detection of Gastric Cancer Risk from X-ray Images
via Soft Voting”, International Technical Conference on Circuits, Systems, Computers, andCommunications (ITC-CSCC), pp.481-483 (2017)222) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Deterioration Level Estimation on
Transmission Towers via Extreme Learning Machine based on Combination Use of Local Receptive Field
and Principal Component Analysis”, International Technical Conference on Circuits, Systems, Computers,and Communications (ITC-CSCC), pp.457-458 (2017)223) Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama: “Effectiveness Evaluation of Imaging
Direction for Estimation of Gastritis Regions on Gastric X-ray Images”, International TechnicalConference on Circuits, Systems, Computers, and Communications (ITC-CSCC), pp.459-460 (2017)
224) Naoki Saito, Takahiro Ogawa, Miki Haseyama: “Identification of Reliable Results for Rubber Material
Property Estimation Using Scanning Electron Microscope Images and Mix Proportions”, International
Technical Conference on Circuits, Systems, Computers, and Communications (ITC-CSCC), pp.265-266

135

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(2017)225) Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Retrieval System of Similar Inspection Records for
Support of Maintenance Inspection in Expressway and Discussions of Evaluation by Experienced
Inspectors”, International Conference on Civil and Building Engineering Informatics (ICCBEI 2017),
pp.190-193 (2017)226) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Distress Classification of Class
Imbalanced Data for Maintenance Inspection of Road Structures in Express Way”, International
Conference on Civil and Building Engineering Informatics (ICCBEI 2017), pp.182-185 (2017)227) Ryota Saito, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Retrieval of Similar Inspection Records
Using Deep Learning Based Image Features in Expressway”, International Conference on Civil andBuilding Engineering Informatics (ICCBEI 2017), pp.186-189 (2017)228) Yoshiki Ito, Takahiro Ogawa, Miki Haseyama: “Personalized Video Preference Estimation Based on Early
Fusion Using Multiple Users Viewing Behavior”, IEEE International Conference on Acoustics, Speech,
and Signal Processing (ICASSP), pp.3006-3010 (2017)229) Takahiro Ogawa, Miki Haseyama: “Exemplar-Based Image Completion via New Quality Measure Basedon Phaseless Texture Features”, IEEE International Conference on Acoustics, Speech, and Signal
Processing (ICASSP), pp.1827-1831 (2017)230) Kento Sugata, Takahiro Ogawa, Miki Haseyama: “Emotion Estimation via Tensor-based Supervised
Decision-level Fusion from Multiple Brodmann Areas”, IEEE International Conference on Acoustics,
Speech, and Signal Processing (ICASSP), pp.999-1003 (2017)231) Sho Takahashi, Miki Haseyama: “Detection of Similar Scenes based on Network Analysis in Soccer
Videos”, 2017 International Workshop on Advanced Image Technology (IWAIT), pp.5A-5 (2017)232) Akira Toyoda, Takahiro Ogawa, Miki Haseyama: “Favorite Image Estimation: EEG-based Extraction ofVisual Features Reflecting Individual Preference”, 2017 International Workshop on Advanced Image
Technology (IWAIT), pp.2A-3 (2017)
233) Masaharu Yoshioka, “WC3: Analyzing the Style of Metadata Annotation Among Wikipedia Articles byUsing Wikipedia Category and the DBpedia Metadata Database”, ISWC 2016 International Workshops:
KEKI and NLP&DBpedia, October 2016 Revised Selected Papers LNCS 10579: Knowledge Graphs andLanguage Technology, pp. 119-136 [OV]234) Masaharu Yoshioka, “Analysis of COLIEE Information Retrieval Task Data”, The Proceedings of the 11th
International Workshop on Juris-Informatics (JURISIN2017), pp. 156-167, The Japanese Society ofArticial Intelligence, 2017 [International Conference]235) Shan Gao, Masakazu Ishihata, Shin-ichi Minato, “Fast Message Passing Algorithm Using ZDD-Based
Local Structure Compilation”, Proceedings of Machine Learning Research vol 73, pp. 117-128, 2017
[OV][Proc]
236) Reona Minoda, Shin-ichi Minato, “Eﬃcient Scenario Verication of Proximity-based Federations among
Smart Objects through Symbolic Model Checking”, Proceedings of the 7th International Joint Conference
on Pervasive and Embedded Computing and Communication Systems (PECCS 2017), pages 13-

136

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21[OV][Proc]
237) Reona Minoda, Masakazu Ishihata, Shin-ichi Minato, “Probabilistic CCRN: Reliability Analysis of
Ubiquitous Computing Scenarios Using Probabilistic Model Checking”, The Eleventh International
Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 85-91[OV][Proc]
238) Teruji Sugaya, Masaaki Nishino, Norihito Yasuda, Shin-ichi Minato, “Fast Compilation of s-t Paths on a
Graph for Counting and Enumeration”, Proc. of the Third Workshop on Advanced Methodologies forBayesian Networks (AMBN 2017), pp. 129-140. Sep. 2017. [OV][Proc]
239) Masaaki Nishino, Norihito Yasuda, Shin-ichi Minato and Masaaki Nagata: “Dancing with Decision
Diagrams: A Combined Approach to Exact Cover,” In Proc. of the 31st AAAI Conference on Artificial
Intelligence (AAAI2017), Feb. 2017. [OV][Proc]
240) Fumito Takeuchi, Masaaki Nishino, Norihito Yasuda, Takuya Akiba, Shin-Ichi Minato and Masaaki
Nagata: “BDD-Constrained A* Search: A Fast Method for Solving Constrained DAG Shortest-Path
Problems,” In Proc. of AAAI-17 Workshop on Symbolic Inference and Optimization (SymInfOpt-2017),
Feb. 2017. [OV][Proc]
241) Jun Kawahara, Takashi Horiyama, Keisuke Hotta, and Shin-ichi Minato: “Generating All Patterns of Graph
Partitions within a Disparity Bound,” In Proc. of the 11th International Workshop of Algorithms andComputation (WALCOM2017), Mar. 2017. [OV][Proc]
2016242) Takuya Takagi, Shunsuke Inenaga, Kunihiko Sadakane, Hiroki Arimura, “Packed Compact Tries: A Fastand Efficient Data Structure for Online String Processing”, Proc. 27th International Workshop on
Combinatorial Algorithm (IWOCA 2016), LNCS, Vol.9843, 213-225, Springer, 2016. (DOI: 10.1007/9783-319-44543-4_17) (Helsinki, Finland, August 1719, 2016) (Also available as: CoRR abs/1602.00422,
arXiv, 2016) [OV] [Proc]
243) Kazuhiro Kurita, Kunihiro Wasa, Takeaki Uno, Hiroki Arimura, “Efficient Enumeration of Induced
Matchings in Graphs without Short Cycles”, Japan Conference on Discrete and Computational Geometory,
Graphs, and Games 2016 (JCDCG^3 2016), Tokyo, Japan, September 2016. [JP, International Conference][Proc]
244) Mayumbo Nyirenda, Hiroki Arimura, Kimihito Ito, “Relaxing the data access bottleneck of geographic bigdata analytics applications using distributed quad trees”, Proc. 5th International Conference on Multimedia
Computing and Systems (ICMCS'16), ID-111, IEEE, 2016. (Palm Plaza Hotel, Marrakech, Morocco, 29
September - 1 October 2016) [OV] [Proc]
245) Kunihiro Wasa, Katsuhisa Yamanaka, Hiroki Arimura, “The Complexity of Induced Tree Reconfiguration
Problems”, Proc. 10th International Conference on Language and Automata Theory and Applications(LATA 2016), Lecture Notes in Computer Science, Vol.9618, Springer, 330-342, 2016. DOI: 10.1007/9783-319-30000-9_26, (Prague, Czech Republic, March 14-18, 2016) [OV] [Proc]
246) Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: “Tracking Hierarchical Structure of Web Video
Groups Based on Salient Keyword Matching Including Semantic Broadness Estimation”, IEEE Global
Conference on Signal and Information Processing (GlobalSIP 2016), pp.1238-1242 (2016)

137

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247) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa and Miki Haseyama: “Distress Classification of Road
Structures via Decision Level Fusion”, 2016 IEEE International Conference on Digital Signal Processing(DSP), pp.589-593 (2016)248) Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Retrieval Method of Similar Inspection Records basedon Distance Metric Learning in Expressway Maintenance”, International Conference on Sustainable
Infrastructure (2016)249) Yuma Sasaka, Takahiro Ogawa, Miki Haseyama: “Multimodal Interest Level Estimation via Variational
Bayesinan Mixture of Robust CCA”, 2016 ACM on Multimedia Conference, pp.387-391 (2016)250) Yoshiki Ito, Takahiro Ogawa, Miki Haseyama: “Novel Video Feature-based Favorite Video Estimation
Using Users' Viewing Behavior and Evaluation”, 2016 IEEE 5th Global Conference on Consumer
Electronics (GCCE), pp.224-225 (2016)251) Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama: “A Tourism Category Classification
Method Based on Estimation of Reliable Decision”, 2016 IEEE 5th Global Conference on Consumer
Electronics (GCCE2016), pp.52-53 (2016)252) Kento Sugata, Takahiro Ogawa, Miki Haseyama: “Estimating Human Emotion Evoked by Visual Stimuli
Using fMRI Data”, 2016 IEEE 5th Global Conference on Consumer Electronics (GCCE), pp.38-39 (2016)253) Shota Hamano, Takahiro Ogawa, Miki Haseyama: “Different Language Association Using Mutual
Information Between Tags and Visual Features”, 2016 IEEE 5th Global Conference on Consumer
Electronics (GCCE), pp.46-47 (2016)254) Susumu Genma, Takahiro Ogawa, Miki Haseyama: “Image Retrieval for Identification of Insects Based on
Saliency Map and Distance Metric Learning”, 2016 IEEE 5th Global Conference on Consumer Electronics(GCCE), pp.50-51 (2016)255) Ryota Saito, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Retrieval of Similar Inspection Records
Based on Metric Learning Using Experienced Inspectors' Evaluation”, 2016 IEEE 5th Global Conference
on Consumer Electronics (GCCE), pp.48-49 (2016)256) Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Decision Level Fusion-based Team
Tactics Estimation in Soccer Videos”, 2016 IEEE 5th Global Conference on Consumer Electronics(GCCE2016), pp.58-59 (2016)257) Daichi Takehara, Ryosuke Harakawa, Takahiro Ogawa, and Miki Haseyama: “Hierarchical Content Group
Detection From Different Social Media Platforms Using Web Link Structure”, 2016 IEEE International
Conference on Image Processing (ICIP), pp.479-483 (2016)258) Soh Yoshida, Takahiro Ogawa and Miki Haseyama: “Graph-based web video search reranking throughconsistency analysis using spectral clustering”, 2016 IEEE International Conference on Multimedia andExpo (ICME), pp.1-6 (2016)259) Robert Wille, Nils Quetschlich, Yuma Inoue, Norihito Yasuda, and Shin-ichi Minato: “Using PiDDs for
Nearest Neighbor Optimization of Quantum Circuits,” In Proc. of the 8th International Conference on
Reversible Computation (RC 2016), (LNCS 9720, Springer), pp. 181-196, Jul. 2016. [OV][Proc]
260) Hirofumi Suzuki, Sun Hao, and Shin-ichi Minato: “Generating All Solutions of Minesweeper Problem

138

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Using Degree Constrained Subgraph Model,” In Proc. of the 2016 International Conference on Parallel &Distributed Processing Techniques & Applications (PDPTA'16), a Workshop session of Mathematical
Modeling and Problem Solving, pp. 356-362, Jul. 2016. [OV][Proc]
261) Reona Minoda, Yuzuru Tanaka, and Shin-ichi Minato: “Verifying Scenarios of Proximity-basedFederations among Smart Objects through Model Checking,” In Proc. of the Tenth International
Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM 2016),
pp. 65-71, Oct. 2016. (Best paper awarded) [OV][Proc]
2-3. Other Publications: Featured in Domestic Journals (in Japanese): #32
2021-2020
1)

Sato, T., Shimada, S., Murakami, H., Watanabe, H., Hashizume, H., Sugimoto, M.: Visible Light Positioning
using Smartphone Ambient Light Sensor, IPJS Journal, Vol.62 (in Japanese, to appear in 2021). †2)

Shimada, S., Hashizume, H., Sugimoto, M.: Visible Light Positioning System for Smartphone using Floorreflected LED Light, IEICE Transactions on Fundamentals of Electronics, Communications and Computer
Sciences, Vol.J104-A, (in Japanese, to appear in 2021). *ii) †3)

Mitake, H., Watanabe, H., Sugimoto, M.: A Method for Recognizing Road Surface Condition based onFootsteps and Inertial Data, IPJS Journal, Vol.61, No.10, pp.1578-1590 (2020, in Japanese). †4)

Amesaka, T., Watanabe, H., Sugimoto, M.: Ear Canal Transfer Function-based Facial Expression Recognition,
IPJS Journal, Vol.61, No.8, pp. 1333-1342 (2020, in Japanese). †5)

前⽥圭介, ⻫藤僚汰, 髙橋翔 ⼩川貴弘, ⻑⾕⼭美紀: "視線データと点検データの正準相関に基づく
道 路 橋 点 検の た め の 類似 デ ー タ 検索 ", ⼟ ⽊ 学会 論 ⽂ 集 F3( ⼟ ⽊ 情 報学 ), vol.76, no.1, pp.74-86(2020)[JP] †6)

狩野芳伸, 吉岡真治, ラベロ ジュリアーノ, キム ミユン, ゴーベル ランディ, 佐藤健: COLIEE : 法
律⽂書の情報抽出および含意関係認識を⾏う国際コンペティション. ⼈⼯知能学会誌, Vol. 35, No. 3,
pp. 377-384, 2020. (解説論⽂)*i) †7)

岡⽥友哉，坂本⼤介，⼩野哲雄 (2021)．スキーポールによる携帯端末操作に向けた ユーザ定義型ジェスチャの設計と認識，情報処理学会論⽂誌，Vol. 62，No. 2（2021/2/15 発⾏予定）†

8)

秋葉 翔太, 崔 明根, 坂本 ⼤介, ⼩野 哲雄, 選択ターゲット候補の半円状再配置によるスマートフ
ォンでの⽚⼿選択操作⼿法の提案, 情報処理学会論⽂誌 Vol.62, No.2 (2021/2/15 発⾏予定) †9)崔明根, 坂本⼤介, ⼩野哲雄, Bubble Gaze Lens：バブルレンズ法の視線操作への適⽤, ⽅法処理学会
論⽂誌 Vol.62, No.2, (2021/2/15 発⾏予定) †201910) 宇野 耕平, 平野 新，嶋⽥ 祥太，渡邊 拓貴，橋⽖ 宏達，杉本 雅則, “変調光照明を⽤いた違法写真
撮影判定⼿法の提案とその評価”，情報処理学会論⽂誌，Vol.61, No.3, 2020 (to appear). [JP]11) ⿑藤晋聖, “空間分割多重伝送⽤光ファイバによる光通信の⼤容量化”, 電⼦情報通信学会通信ソサイ
エティマガジン, no. 51, Winter, pp. 166-176, 2019. [JP]12) 藤後 廉, 間部 克裕, ⼭道信毅, ⼤泉晴史, ⼩川 貴弘, ⻑⾕⼭ 美紀, 加藤 元嗣, 坂本 直哉: “胃バリ139

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ウム検査における AI による Helicobacter pylori 診断”, Helicobacter Research, vol.23, no.2, pp.133137(2019) [JP]13) ⻑⾕⼭ 美紀, ⼩川 貴弘, ⾼橋 翔, 原川 良介: “センサから得られる視聴⾏動データを活⽤したユー
ザの関⼼推定の⾼度化”画像ラボ, vol.30, no.7, pp.8-12(2019) [JP]14) ⻑⾕⼭ 美紀: “AI って何だろう？”2020 ⾼校⼊試 合格データ特集 道新受験情報, pp.19-22(2019)[JP]15) 平⽥ 健司, 藤後 廉, ⼩川 貴弘, ⻑⾕⼭ 美紀, 志賀 哲: “核医学におけるディープラーニングを⽤いた画像診断”画像処理 INNERVISION (2019) [JP]16) 栗原 聡, ⻑⾕⼭ 美紀: “⼈と共⽣する AI ⾰命 活⽤事例から⾒る⽣活・産業・社会の未来展望”pp.2129(2019) [JP]17) ⻫藤 僚汰，⾼橋 翔，⼩川 貴弘，⻑⾕⼭ 美紀: “熟練技術者の判定に基づいた道路橋における類似点
検データの検索”, ⼟⽊学会論⽂集 F3(⼟⽊情報学), vol.74, no.1, pp.67-77 (2018)[JP]
18) ⼭⼝歌奈⼦, 東中雅嗣, 佐野裕康, 岡村敦, ⼤鐘武雄, ⻄村寿彦, “包絡線変動量を抑圧する位相回転
送信ダイバーシチを適⽤した狭帯域パイロットレス同期検波 FSK ⽅式”, 電⼦情報通信学会論⽂誌，
早期公開論⽂（早期公開⽇:2019/10/28）. [JP]19) 村上 弘晃, 中村 将成，橋⽖ 宏達，杉本 雅則, “鏡像スピーカを⽤いたスマートフォン⾼精度 3 次元測位⼿法”，情報処理学会論⽂誌，Vol.60, No.12, pp.2314-2324, 2019. [JP]20) 嶋⽥ 祥太，橋⽖ 宏達，杉本 雅則, “CMOS イメージセンサを⽤いた OFDM ⾼速可視光通信”，電⼦情報通信学会論⽂誌，Vol. J102-B, No. 8, pp.605-613, 2019. [JP] *ii)21) ⻑⽥直樹, “ヤポネシア⼈の歴史の解明が医学にもたらすもの”．実験医学 37: 926-929 (2019). [JP]22) ⼭岸 誠知, ⽇景 隆,

久野 伸晃,

中村 光貴,

⼭⽥渉,

鷹取 泰司: “数値シミュレーションを⽤いた 26 GHz 帯屋内伝搬における⼈体遮蔽特性推定法についての⼀検討,” 電⼦情報通信学会論⽂誌
C, Vol.J102-C, No.5, pp.131-138, May 2019. [JP]201823) ⻑⾕⼭ 美紀: “バイオミメティクス画像検索:情報科学が繋ぐ博物学とナノテクノロジー”, 持続可能社会を拓くバイオミメティクス--⽣物学と⼯学が築く材料科学, pp.38-45 (2018) [JP]24) ⻑⾕⼭美紀, 川村圭, 多良島周平, 新井啓之: “メディア⼯学の研究動向”, 映像情報メディア学会誌,
vol.72, no.2, pp.241-246 (2018) [JP]25) 齋藤 剣聖, ⼩川 恭孝, ⻄村 寿彦, ⼤鐘 武雄, “MIMO SC-FDE における受信ウェイトの補間精度の劣化とその軽減法,” 電⼦情報通信学会論⽂誌 B, Vol. J101.B, No. 7, pp.570-573, Jul. 2018. doi:
10.14923/transcomj.2017WFL0001 [JP]26) ⼤鐘武雄, ⻄村寿彦, ⼩川恭孝, “5G を実現する MIMO 技術,” 電⼦情報通信学会誌, Vol.101, No.11,
pp.1117-1122, 2018. ISSN: 0913-5693 (Print) / ISSN: 2188-2355 (Online)[JP]201727) ⻑⾕⼭美紀: “農業ビッグデータ解析基盤の構築 -発想⽀援型検索による害⾍同定⽀援の試み-”, 情報処理, vol.58, no.9, pp.798-801 (2017) [JP]28) ⻑⾕⼭ 美紀: “ビッグデータ解析による新しいインフラ維持管理 ー 画像解析による河川管理施設の点検効率化に関する研究 −”, 開発こうほう, no.646, pp.36-39 (2017) [JP]140

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201629) ⾼橋 翔，⻑⾕⼭ 美紀: “サッカー映像における試合内容の理解を促すデータの可視化”, 映像情報メディア学会誌, vol.70, no.5, pp.722-724 (2016) [JP]30) ⻫藤直輝，⼩川貴弘，浅⽔仁，⻑⾕⼭美紀: “画像共有サービスに投稿される画像の観光名所に関する
カテゴリー分類”, 電⼦情報通信学会論⽂誌 D, vol.J99-D, no.9, pp.848-860 (2016) [JP]31) ⻑⾕⼭ 美紀: “発想⽀援型検索と異分野連携がもたらす可能性”, 化学経済, vol.63, no.11, pp.42-46(2016) [JP]32) 湊真⼀, “私は何がしたかったのか，そしてどのように進んできたのか（レクチャーシリーズ「つながりが創発するイノベーション」第 7 回）,” ⼈⼯知能学会誌 ,Vol. 31, No. 3, pp. 452-463, May. 2016.
[JP]

2-4. Other Publications: Books Published: #5
International
2020
1)

Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama: "How to Make Artificial Intelligence More
Democratic", SCIENTIFIC AMERICAN (2021) †2)

Masaharu Yoshioka and Hideo Joho : Temporal Information Access. In Evaluating Information
Retrieval and Access Tasks: NTCIR's Legacy of Research Impact, Tetsuya Sakai, Douglas W. Oard,
and Noriko Kando (eds), pp. 127-141, Springer Singapore, Singapore, 2020. [OV]*i) †
2018

3)

Convertino M and Valverde JL, “Critical Values: Collective Information and Decision Analytics”, 2019,
proposed to Springer Series ‘’Risk Governance and Society’’, in review [OV] [Books in review]*Not accepted and excluded from the final counts.

4)

Travis D., Convertino M., Shaffer C., Gillespie T., Alpern J., Stauffer W., Robertson C., Kennedy S., Craft
M., “Biodiversity and Health, Engineering Ecosystem Heath via Science and Technology”, in ‘’Beyond
One Health”, Editors: Herrmann JA and Johnson-Walker YJ, John Wiley Sons, 2018 [OV]Japanese20195) ⻑⽥直樹, “進化で読み解く バイオインフォマティクス⼊⾨” 森北出版（2019）．[Books]
20176) 有村 博紀, “系列マイニング”, ⼈⼯知能学⼤事典, ⼈⼯知能学会編, 6 章-99 節, pp. 469-472, 共
⽴出版, Jul. 2017. [Books]

5. Awards Received: #55 in totalAwards at International Conferences: #34
2021-2020
1)

Guang Li, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Complexity evaluation of medical image data forclassification problem based on spectral clustering", 2020 IEEE 9th Global Conference on Consumer

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Electronics (GCCE 2020), pp.112-114 (2020) †2)

Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Important scene prediction of
baseball videos using twitter and video analysis based on LSTM", 2020 IEEE 9th Global Conference on
Consumer Electronics (GCCE 2020), pp.85-86 (2020) †3)

Saya Takada, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Question answering for estimation of seen
image contents from multi-subject fMRI responses", 2020 IEEE 9th Global Conference on Consumer
Electronics (GCCE 2020), pp.763-764 (2020) †4)

Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Face synthesis via user manipulation ofdisentangled latent representation", 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE2020), pp.1-2 (2020) †5)

Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Interest level estimation based onfeature integration considering distribution of partially paired user’s behavior, videos and posters", 2020
IEEE 9th Global Conference on Consumer Electronics (GCCE 2020), pp.558-559 (2020) †6)

Kaito Hirasawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Important scene detection based on
anomaly detection using long short-term memory for baseball highlight generation", 2020 IEEE
International Conference on Consumer Electronics-Taiwan (ICCE-TW 2020) (2020) †7)

Takahiro Ogawa, Kento Sugata, Ren Togo, Miki Haseyama: "Multi-classifier Decision: Integration ofMultiple Brain Activity-based Classifications", ITE Transactions on Media Technology and Applications,vol.7, no.1, pp.36-44 (2020) †8)

Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Query is GAN: scene retrieval withattentional text-to-image generative adversarial network", IEEE Access. The 2020 IEEE Section Best Paper
Award (2021) †9)Genki Suzuki, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: "Team tactics estimation in soccer videos
based on a deep extreme learning machine and characteristics of the tacctics ", IEEE Access. The 2020
IEEE Sapporo Section Encouragement Award (2021) †10) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama: "Human emotion estimation using multimodal variational autoencoder with time changes", 2021 IEEE 3rd Global Conference on Life Sciences
and Technologies (LifeTech 2021), Excellent Poster (On-site) Award Winner: Bronze Prize (2021) †11) Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: "Interactive re-ranking for cross-modal
retrieval based on object-wise question answering ", ACM International Conference on Multimedia in Asia.
Best Paper Runner-Up Award (2021) †12) Nakamura, M., Hashizume, H., Sugimoto, M., SENSORDEVICES 2020 Best Paper Award, "Simultaneous
Localization and Communication Methods using Short-time and Narrow-band Acoustic Signals"
November, 2020. †13) Matteo Convertino, Hult Prize Hokudai Campus challenge (second place and invitation to the Tokyo
regional competition); Team SEA2SEE with students Galbraith E. (IST), Li J. (IST), Garcon EJ (Agric.),& Chebbi N (Chem Eng), December 2020.
14) Matteo Convertino, Reviewer Award for MDPI Journals Sustainability, Symmetry, and Climate, Jan 2020.

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201915) Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama: Outstanding Prize IEEE GCCE 2019
Excelent Demo! Award,”Voice-input multimedia information retrieval system based on text-to-image
GAN”2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019), pp.967-968(2019)16) Megumi Kotera, Ren Togo, Takahiro Ogawa, Miki Haseyama: Silver Prize IEEE GCCE 2019 Excelent
Poster Award, “Aesthetic style transfer through text-to-image synthesis and image-to-image translation
2019”IEEE 8th Global Conference on Consumer Electronics (GCCE 2019), pp.492-493(2019)17) Yusuke Akamatsu, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: Silver Prize IEEE GCCE 2019
Excelent Paper Award, “Estimating viewed image categories from fMRI activity via multi-view bayesian
generative model”2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2019), pp.129130(2019)18) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: 2nd Prize IEEE Lifetech 2019
Excellent Paper Award, “Estimation of Visual Attention via Canonical Correlation between Visual and
Gaze-based Features”, 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech2019), pp.229-230 (2019)19) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: The 2018 IEEE Sapporo Section
Encouragement Award, “Automatic Estimation of Deterioration Level on Transmission Towers via Deep
Extreme Learning Machine Based on Local Receptive Field”, IEEE International Conference on Image
Processing (ICIP 2017), pp.2379-2383 (2019)20) Akira Toyoda, Takahiro Ogawa, Miki Haseyama, The 2018 IEEE Sapporo Section Encouragement Award,“MvLFDA-based Video Preference Estimation Using Complementary Properties of Features”, The 2018
IEEE Sapporo Section Encouragement Award (2019)21) Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama: Best Paper Award, “Classification of
Tourism Categories Based on Heterogeneous Features Considering Existence of Reliable Results”, The
2019 joint International Workshop on Advanced Image Technology & International Forum on Medical
Imaging in Asia (2019)22) Masanori Sugimoto, Best Paper Award in IEEE KST 2019 (January 23-26, 2019, Phuket, Thailand)“Detecting Text in Manga using Stroke Width Transform”
23) Yoshihiro Hirose, “Outstanding Poster Award 1st Prize”, Data Science Statistics & Visualisation(DSSV2019), Kyoto. (2019 August)24) Takashi Hikage, Distinguished Contributions Award, IEICE Communication Society (2019.9.11)
25) Takashi Hikage, The Best Poster Presentation Award, PJWWRAT2019 (2019.12.5)
201826) Tomoki Haruyama, Sho Takahashi, Takahiro Ogawa, Miki Haseyama, 1st Prize IEEE GCCE 2018
Excellent Poster Award, “Estimation of Important Scenes in Soccer Videos Based on Collaborative Use of
Audio-Visual CNN Features”, 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018),
pp.675-676 (2018)27) Yuya Moroto, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama: IEEE GCCE 2018 Outstanding Paper

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Award, “User-centric Visual Attention Estimation Based on Relationship Between Image and Eye GazeData”, 2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018), pp.44-45 (2018)28) Keisuke Maeda, Sho Takahashi, Takahiro Ogawa, Miki Haseyama: “Distress Classification of Road
Structures via Decision Level Fusion”, 2016 IEEE International Conference on Digital Signal Processing(DSP), pp.589-593 (2018)201729) Yui Matsumoto, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: IEEE GCCE2017 Outstanding
Poster Award, “Construction of Network Using Heterogeneous Social Metadata for Music Video
Recommendation”, 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE2017), pp.316-317(2017)
30) Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama: The 2016 IEEE Sapporo Section Encouragement
Award, “Extraction of hierarchical structure of Web communities including salient keyword estimation for
Web video retrieval” (2017)31) Akira Toyoda, Takahiro Ogawa, Miki Haseyama: Best Paper Award, “Favorite Image Estimation: EEGbased Extraction of Visual Features Reflecting Individual Preference”, 2017 International Workshop on
Advanced Image Technology (IWAIT), pp.2A-3 (2017)32) Kunimasa Saitoh, “IEEE Photonics Society Distinguished Lecturers Award”, 2017
201633) Naoki Saito, Takahiro Ogawa, Satoshi Asamizu, Miki Haseyama: 1st Prize IEEE GCCE 2016 Excellent
Poster Award, “A Tourism Category Classification Method Based on Estimation of Reliable Decision”,
2016 IEEE 5th Global Conference on Consumer Electronics (GCCE2016), pp.52-53 (2016)34) Reona Minoda, Yuzuru Tanaka, and Shin-ichi Minato: Best paper award, “Verifying Scenarios of
Proximity-based Federations among Smart Objects through Model Checking,” In Proc. of the TenthInternational Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies(UBICOMM 2016), pp. 65-71, Oct. 2016.

(end)

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References

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146

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Global Institution for Collaborative Research and Education (GI‐CoRE)
Final Evaluation for the Global Station for Big Data and Cybersecurity projects
1. Aims
The Global Institution for Collaborative Research and Education (GI-CoRE) shall implement an
external evaluation of the research, education and organizational framework of the Global Station for
Big Data and Cybersecurity projects which started on April 1, 2016. As the projects have welcomed
the final (fifth) year of the implementation period upon the Fiscal Year 2020, the feedback of thisevaluation shall be used to improve the future project.
2. Evaluation Structure
A "Hokkaido University Global Institution for Collaborative Research and Education External
Evaluation Committee" shall be established in Big Data and Cybersecurity Global Station inaccordance with the External Evaluation Implementation Guidelines for the Hokkaido University
Global Institution for Collaborative Research and Education Global Station (Document 2). Allevaluations and reports shall be undertaken in English.
□ Global Station for Big Data and Cybersecurity External Evaluation Committee
Candidates from Big Data and Cybersecurity GS: 2 foreign members, 1 Japanese member*When the evaluation is completed, the GI-CoRE Steering Committee shall receive a report fromthe Committee chair.
3. Evaluation Method□The External Evaluation Committee shall check the contents of the Research Progress Report(Document 3) sent in advance from HU before implementing the investigation, and shall evaluate
the evaluation items prescribed in Document 4.
□A 5-level evaluation ratings (S to D) and comments shall be obtained for each "Evaluation Item".
Evaluation
Evaluation Explanation
Ratings
S
Achieved outcomes surpassed the original plan (Outstanding)A
B
C
D

Good progress has been maintained and expected outcomes havebeen achieved (Excellent)
Most expected outcomes have been achieved with some slight delays(Good)
Although certain outcomes were achieved, overall results wereinsufficient (Satisfactory)
No expected outcomes were achieved (Unsatisfactory)

4. Required Expenses
Travel expenses (only when applicable) and honoraria shall be provided to the Committee Members inaccordance with HU regulations. It will be arranged and covered by Global Station for Big Data andCybersecurity, Hokkaido University depending on the situation of COVID-19.

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5. Publishing of Evaluation Results
Evaluation of this project shall be broadly announced, with the results both published on the relevant
HU websites and published as booklets which are sent to external organizations such as the Japanese
Ministry of Education, Culture, Sports, Science and Technology.

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GI‐CoRE Global Station External Evaluation ScheduleYear andAgendaMonth
Fiscal Year 2019 (2019‐2020)
November Selection/Arrangement of the Evaluation Committee Members*Criteria: 2 foreign and 1 Japanese members(candidates who can conduct evaluation in English)*Confirmation of affiliation, main achievements, contact details, etc.
December GI‐CoRE Steering Committee #23*Fixing overviews of evaluation items, evaluation structure, schedule, etc.
*Fixing the Evaluation Committee Members
January to *Starting to create 2020 Research Progress Report (in English)
March *Official appointment request (letters from the GI‐CoRE Director)*Fixing evaluation forms
Fiscal Year 2020 (2020‐2021)
April Commission of Evaluation Committee Members
May Preparation of On‐site Investigation
June Distribution of Research Progress Report to Committee Members
Document screening by Committee Members
July Online meeting via Zoom July 7th
Online investigation based on the document screening
August Submission of Results of the Evaluation from each Committee to the Chair
Each Evaluation Committee Member shall forward their evaluation reports,based on the document screening and on‐line meeting
September to Submission of Summary Report and Results of the Evaluation Committee
November The Chair shall summarize the Evaluation from each Committee and makea report
December GI‐CoRE Steering Committee #27*Report of the results of the Evaluation from the External Evaluation
Committee Members
March Expiration of the GSB project under the GI‐CoRE System
Fiscal Year 2021 (2021‐2022)
April Internalization of the GSB project into the affiliated faculty
July

Publication of the Final Evaluation Report149

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150

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Hokkaido University
Global Institution for Collaborative Research and Education (GI‐CoRE)
External Evaluation Implementation Guidelines for the Global Stations
December 15, 2015
Establishment of the Global Institution for Collaborative Research and Education Steering Committee
1. Purpose
These implementation guidelines shall provide the necessary matters for the
implementation of evaluation of the Global Station by non-University affiliated persons(hereinafter the “GS External Evaluation”) of the Hokkaido University Global Institution for
Collaborative Research and Education (GI-CoRE).
2. Committee(1) The "Hokkaido University Global Institution for Collaborative Research and Education
External Evaluation Committee (hereinafter the "Committee")" shall be established by GICoRE in order to perform the matters prescribed in each of the following items.
(i) Implementation of GS External Evaluation(ii) Matters related to the creation and publishing of the report pertaining to the GS
External Evaluation(2) A Committee shall be established for each Global Station that is target for external
evaluation.
3. Composition(1) The Committee shall be composed of third parties other than constituent members of
Hokkaido University, and designated by the Director of GI-CoRE from persons prescribedin each of the following items.
(i) Person designated by the Director of GI-CoRE who is an expert both within and outside
Japan in the research field of the Global Station to be externally evaluated(ii) Persons whom the Director of GI-CoRE deems necessary(2) The Committee members prescribed in the preceding paragraph shall be commissionedby the Director of GI-CoRE after approval by the GI-CoRE Steering Committee.
4. Term of Office(1) The term of office for Committee Members shall be 1 year. However, if a Committee
Member vacancy occurs, the term of office of the successor shall be the remaining term of
the predecessor.
(2) Committee Members may be reappointed.
5. Committee Chair(1) A Committee Chair shall be appointed and selected through mutual election by theCommittee members.
(2) The Committee Chair shall call a Committee meeting as required, and shall chair the said
meeting.

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6. Proceedings(1) A Committee meeting may not be held unless a majority of the members are present.
(2) Committee meeting proceedings shall be decided by a majority of the attending members.
In case of a tie, the Committee Chair shall decide the issue.
7. Implementation of GS External Evaluation(1) The Committee shall implement the GS External Evaluation as prescribed in thefollowing Article.
(2) The Committee may hear the opinions of persons concerned and implement firsthandinvestigations related to the implementation of the GS External Evaluation.
8. Evaluation Items
The Committee shall evaluate the items prescribed by GI-CoRE in each of the following
items.
(1) Items related to research(2) Items related to education(3) Items related to the structure of the research and education center(4) Other items deemed necessary by the Committee
9. Creation and Publishing of the Report
The Committee shall collate the evaluation results prescribed in the preceding paragraphand publish the results in a report.
10. Response to Evaluation Results
The Director of GI-CoRE shall promptly work to implement improvements in view of thereport prescribed in the previous paragraph for items in which improvements are deemednecessary.
11. General Affairs
General affairs for the Committee shall be processed by the Division of International
Planning, International Affairs Department.
12. Miscellaneous Provisions
Necessary matters concerning GS External Evaluation other than those prescribed withinthese implementation guidelines shall be prescribed separately by the GI-CoRE Steering
Committee.
Supplementary Provisions
These guidelines shall come in force on 12 December 2017.
Supplementary Provisions
These guidelines shall come into force on March 7, 2019 and shall be applied from July 1, 2018.

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REGULATIONS FOR THE HOKKAIDO UNIVERSITYGLOBAL INSTITUTION FOR COLLABORATIVE RESEARCH AND EDUCATIONHU Doc. No.151
April 1, 2014
(Purpose)
Article 1 These Regulations shall prescribe the organization and administration of the
Hokkaido University Global Institution for Collaborative Research and Education(hereinafter referred to as "the Institution for Research and Education"), based upon theRules Concerning the Organization of Hokkaido University (HU Doc. No. 31 of 2004),
Article 37(4).
(Objectives)
Article 2 The objectives of the Institution for Research and Education shall be to invite
teaching staff from Japan and overseas with world-class education and research results, topromote international collaborative research and international collaborative education(hereinafter referred to as "international collaborative research and education") that
capitalizes upon the distinctive characteristics of Hokkaido University (hereinafter referred
to as the "University"), and to provide support for international collaborative research being
furthered independently by faculties or schools.
(Employees)
Article 3 A Director and other necessary teaching staff shall be placed in the Institution for
Research and Education.
(The Director)
Article 4 The President shall be appointed as the Director of the Institution for Researchand Education.
2. The Director shall supervise the work of the Institution for Research and Education.
(The assistant director)
Article 5 An assistant director shall be placed in the Institution for Research and Education.
2. A vice president designated by the President shall be appointed as the assistant director.
3. The assistant director shall assist the Director in his or her duties and shall take over those duties in the event of the latter being incapacitated.
(Global stations)
Article 6 The following global stations shall be placed in the Institution for Research and
Education to promote international collaborative research and education that capitalizes
upon the distinctive characteristics of the University.
(1) The Global Station for Soft Matter(2) The Global Station for Big Data and Cybersecurity(3) The Global Station for Arctic Research(4) The Global Station for Biosurfaces and Drug Discovery
2. Full-time teaching staff from the University (including specially appointed academic staff
who come under each item of Article 3 of the Hokkaido University Specially Appointed
Academic Staff Regulations (HU Doc. No. 35 of 2006). The same applies to Article 7(2)below.) and teaching staff invited from Japan and overseas shall be placed in the Institution
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for Research and Education.
3. The period for which a global station is established shall be five years. However, thisperiod can be extended within five years if the steering committee provided for in Article 8
deems it necessary.
(Global station leaders)
Article 7 A global station leader shall be placed in each of the global stations referred to in
the items of Article 6(1).
2. The global station leader shall be one of the teaching staff of the said global station who
has been designated by the Director.
3. The global station leader shall supervise the work of the said global station under the ordersof the Director.
4. The term of office of the global station leaders shall be three years or less, and they can bereappointed.
(Steering Committee)
Article 8 A steering committee shall be placed in the Institution for Research and Education
to deliberate important matters concerning the said institution.
2. The organization and administration of the steering committee shall be prescribed
separately.
(Administration)
Article 9 The administrative work of the Institution for Research and Education shall beprocessed in the Division of International Planning, the International Affairs Department.
(Miscellaneous provisions)
Article 10 In addition to what is prescribed in these Regulations, necessary mattersregarding the operation of the Institution for Research and Education shall be prescribed
separately by the President after approval by the steering committee.
Supplementary Provisions
These Regulations come into force on April 1, 2014.
Supplementary Provisions
These Regulations come into force on April 1, 2015.
Supplementary Provisions
These Regulations come into force on April 1, 2016.
Supplementary Provisions
These Regulations come into force on July 1, 2018.
Supplementary Provisions
These Regulations come into force on March 1, 2020.
Supplementary Provisions
These Regulations come into force on April 1, 2020.

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REGULATIONS FOR THE GLOBAL INSTITUTIONFOR COLLABORATIVE RESEARCH AND EDUCATION STEERING COMMITTEE
HU Doc. No. 152
April 1, 2014
(Purpose)
Article 1 These regulations shall provide for the necessary matters concerning theorganization and administration of the Global Institution for Collaborative Research and
Education Steering Committee (hereinafter referred to as "the committee"), based upon
Article 8(2) of the Regulations for the Global Institution for Collaborative Research and
Education (HU Doc. No. 151 of 2014, "Regulations for the Institution for Education andResearch" in Article 3).
(Topics for Deliberation)
Article 2 The committee shall deliberate on the issues set forth in item (6) through item (10)of Article 2 of the National University Corporation Hokkaido University Agenda for
Hearing with Faculty Council Rules (HU Doc. No. 42 of 2015, referred to as “Hearing
Rules” in the following paragraph) and deliver opinions to the President.
2. In addition to the matters specified in the preceding paragraph, the committee shalldeliberate the following matters pertaining to the Hokkaido University Global Institution
for Collaborative Research and Education (hereinafter referred to as "the Institution for
Research and Education" in (5) below).
(1) Matters regarding personnel affairs of the faculty (excluding matters set forth in item (6)through item (10) of Article 2 of the Hearing Rules).
(2) Matters regarding the establishment, reform or termination of global stations.
(3) Matters regarding the evaluation of the educational and research activities of global
stations.
(4) Matters regarding budgets.
(5) Other important matters pertaining to the administration of the Institution for Researchand Education.
(Structure)
Article 3 The committee shall consist of the following members:(1) The director of the Global Institution for Collaborative Research and Education(referred to as "the director" in Article 5)(2) The assistant director of the Global Institution for Collaborative Research and Education(referred to as "the assistant director" in Article 5)(3) One vice president designated by the President (excluding the person mentioned in theprevious item)(4) One dean or director from each of the following categories (a-d), each of whom shall be
designated by the Presidenta) The Graduate School of Law, the Faculty of Education, the Research Faculty ofMedia and Communication, the Faculty of Economics and Business, the Faculty of
Humanities and Human Sciences, the Faculty of Public Policy

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b) The Faculty of Fisheries Sciences, the Faculty of Environmental Earth Science, theFaculty of Science, the Research Faculty of Agriculture, the Faculty of Advanced Life
Science, the Faculty of Engineering, the Faculty of Veterinary Medicine, the Faculty ofInformation Science and Technologyc) The Faculty of Pharmaceutical Sciences, the Faculty of Health Sciences, the Faculty of
Medicine, the Faculty of Dental Medicine, Hokkaido University Hospitald) Each affiliated research institute, each research center, the Field Science Center for
Northern Biosphere(5) Each global station leader as prescribed in Article 7 of the Regulations for the Institution
for Education and Research(6) Other persons whom the President deems appropriate
2. The President shall appoint the committee members mentioned in the preceding item (6)(Term of Office)
Article 4 The terms of office of the committee members indicated in paragraph 1(4) andparagraph 1(6) of the previous article shall be two years. However, the term of office of
substitute committee members shall be the remaining term of office of the previous
committee member.
2. The committee members indicated in the preceding paragraph may be reappointed.
(Committee Chair)
Article 5 The director shall be appointed as the committee chair.
2. The committee chair shall call committee meetings and preside over the said meetings.
3. The assistant director shall take over the director's duties in the event of the latter being
incapacitated.
(Proceedings)
Article 6 The committee cannot validly convene unless at least two-thirds of the committee
members are present.
2 Committee proceedings, other than those prescribed separately, shall be decided by the
majority vote of the attending committee members.
(Attendance of Persons Other Than Committee Members)
Article 7 In cases deemed necessary by the committee, persons other than committee
members may be permitted to attend committee meetings, and explanations or opinions of
the said persons may be heard.
(Committees on Special Issues)
Article 8 Committees on special issues may be established within the committee whennecessary in order to deliberate specialized matters.
(General Affairs)
Article 9 The administrative affairs of the committee shall be processed in the Division ofInternational Planning, the International Affairs Department.
(Miscellaneous Provisions)
Article 10 In addition to what is prescribed in these regulations, necessary mattersregarding the operation of the committee shall be prescribed by the said committee.

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Supplementary Provisions
These regulations come into force on April 1, 2014.
Supplementary Provisions (HU Doc. No. 196 of April 1, 2015)
These regulations come into force on April 1, 2015.
Supplementary Provisions (HU Doc. No. 191 of October 1, 2016)
These regulations come into force on October 1, 2016.
Supplementary Provisions (HU Doc. No. 163 of April 1, 2017)
1. These regulations come into force on April 1, 2017.
2. The dean of the Graduate School of Dental Medicine who was specified as a committee
member in c) of paragraph 1(4) of Article 3 prior to the revision (hereinafter referred to as“the former committee member” in this paragraph) shall be deemed to have been
appointed as a committee member under the revised regulations in c) of paragraph 1(4) of
Article 3 on the enforcement date of these regulations. The term of office of the said
member shall be the remaining term of office of the former committee member on theenforcement date, notwithstanding the revised provisions of Article 4(1).
Supplementary Provisions (HU Doc. No. 182 of June 20, 2017)
These regulations come into force on June 20, 2017 and apply retroactively from April 1,
2017.
Supplementary Provisions (HU Doc. No. 98 of July 1, 2018)
These regulations come into force on July 1, 2018.
Supplementary Provisions (HU Doc. No. 134 of April 1, 2019)
1. These regulations come into force on April 1, 2019.
2. The dean of the Graduate School of Letters who was specified as a committee member inc) of paragraph 1(4) of Article 3 prior to the revision (hereinafter referred to as “theformer committee member” in this paragraph) shall be deemed to have been appointed as
a committee member under the revised regulations in c) of paragraph 1(4) of Article 3 onthe enforcement date of these regulations. The term of office of the said member shall be
the remaining term of office of the former committee member on the enforcement date,notwithstanding the revised provisions of Article 4(1).

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158

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Final Evaluation Report | Global Station for Big Data and Cybersecurity, GI-CoRE, Hokkaido University

外部評価報告書

Published by:

発

Global Institution for Collaborative Research

国際連携研究教育局（GI-CoRE）

行：

Global Station for Big Data and Cybersecurity,

北海道大学

and Education (GI-CoRE),

ビッグデータ・サイバーセキュリティグローバルステーション

Website: https://gi-core.oia.hokudai.ac.jp/gsb/

ウェブサイト : https://gi-core.oia.hokudai.ac.jp/gsb/

Hokkaido University

名称未設定-4 2

July 2021

Final Evaluation Report

2021/11/19 16:41