Shohei Hidaka
School of Knowledge Science

Phone: (+81) 761-51-1725

Japan Advanced Institute of Science and Technology

1-1 Nomi, Asahidai, Ishikawa,
Ishikawa 923-1292, Japan.

shhidaka@jaist.ac.jp
http://www.jaist.ac.jp/~shhidaka/

Shohei Hidaka, Ph. D. is an Associate Professor in the School of Knowledge Science, the Japan
Advanced Institute of Science and Technology, Japan, and the principal investigator in the cognitive
computation lab. His work is centered on theorization and computational modeling of human semantic cognition. Specifically, he has done theoretical and empirical research on language learning,social interaction, and embodied cognition. His approach is based on machine learning, data mining,statistical modeling, information theory, nonlinear time series analysis, and so on. Even with thesepowerful computational tools, however, even a tiny bit of ”human computation” is still mysterious.
Education
Ph.D. Informatics, Kyoto University, 2007
Thesis: “A Geometric Model of Categorization Space for Lexical Acquisition”.
M.A. Informatics, Kyoto University, 2004
Thesis: “The Linguistic Category Influence on the Children’s Bias of Word Acquisition”.
B.A. Biology, Kyushu University, 2002
Thesis: “Mathematical Analysis of Geological Heterogeneity Eﬀects on the Distribution of Species”.
Research Experience
Associate professor
2017 April – present
Japan Advanced Institute of Science andIshikawa, Japan
Technology
Mathematical modeling and psychological experiment of language development and bodily dynamical systems.
Assistant professor
2010 April – 2017 MarchJapan Advanced Institute of Science andIshikawa, Japan
Technology
Mathematical modeling and psychological experiment of language development and bodily dynamical systems.
Visiting scholar
Indiana University
Mathematical modeling and psychological experiment of language development.

2012
Bloomington, IN

Post-Doctoral Research Fellow
2008 April –2010 March
National Institutes of HealthIndiana University
Mathematical modeling and psychological experiment of language development.
Research Fellow
2006 April – 2008 MarchJapanese Society for the Promotion of Science
Kyoto University
Mathematical modeling of language development and object recognition.
Teaching Experience
1. Lecturing a graduate level introductory class “Introduction to Cognitive Science” (認知科学入門/認
知科学概論) in JAIST in the spring/summer semester in 2011 – 2018.

2. Hosting a JAIST Summer School 2018 (日高昇平・鳥居拓馬・布山美慕 (2018) JAIST サマースクー
ル 2018「計算論的認知科学入門 ? 心の哲学、実験から機械学習まで」)
3. Hosting two graduate students from Indiana University visiting to Japan Advanced Institute of
Sciences for their JSPS summer projects in 2011 and 2012. Hosting a research scholar from Indiana
University from August to November in 2013.
4. Lectures for Cognitive Science Spring Seminars 2012 and 2014 in Malta University.
5. Tutorial on statistical modeling in cognitive sciences (JCSS SIG-LAL): 日高 昇平 & 西田 豊 (2012).
統計的モデルの考え方：確率分布から多変量解析まで, 日本認知科学会・対話と学習研究会・第 46 回
研究会.
6. Supervising six graduate students for their minor thesis in 2010, 2011, 2012, and 2013.
7. Lecture series in JAIST Summer School 2011 (日高昇平・白肌邦生 (2011) JAIST サマースクール
2011「知識科学のフロンティア：生体計測がつなぐ認知神経科学とサービス経営」)
8. Supervising three graduate students (on the research projects on brain imaging), Spring, Summer,
and Fall 2010 in Indiana University.
9. Research assistant (Introductory class of knowledge science: 知識科学概論 I), Spring 2010, 2011,2012, 2013, 2014, and 2015.
10. Supervising four research assistants (on the research projects of cognitive development), Indiana
University, Spring, Summer, Fall 2009, and Spring 2010.
11. Teaching Assistant, Advanced Informatics (Basic Neural Network Modeling), Kyoto University,
Spring 2004.
Social contributions
1. Volunteer activity for non-typical developing children since May 2010-2011 (Komatsu Municipal
Hospital).
2. Program committee of International Conference Development and Learning (2010).
3. Program committee of the Thirty Seventh Annual Meeting of the Cognitive Science Society (CogSci2015).
4. 日本認知科学会第 29 回大会プログラム委員 (2012).
5. 日本認知科学会第 34 回大会プログラム委員長 (2016-2017).
6. 日本認知科学会第 34 回大会プログラム委員 (2017-2018).
7. 日本認知科学会運営委員 (2013-2017).
8. 日本認知科学会常任運営委員 (2017-2018).
9. 論文誌「認知科学」編集委員 (2015-2018).
10. 論文誌「認知科学」編集幹事 (2019-2023).
11. 日本認知科学会研究分科会間合い研究会幹事 (2014-2017)12. 日独先端科学 (Japan-Germany Frontier of Science) シンポジウムの第 13 回イントロダクトリースピー
カー, 第 14 回企画委員 (PGM)
13. 日本認知科学会研究分科会間合い研究会幹事 (2014-2017)
14. 電気情報通信学会会誌編集委員 (2014-2016).
15. 知識供創フォーラム Comittee member (2014-2018).
16. 野々市市立菅原小学校 PTA 本部役員 (2015-2017).
17. 野々市市立菅原小学校 PTA 副会長 (2018-2019).
18. 野々市市立菅原小学校 PTA 会長 (2019-2020).

Membership
Membership in Japanese Cognitive Science Society (since April 2004).
Membership in Cognitive Science Society (since August 2006).
Membership in Japanese Society for Artificial Intelligence (since April 2013).
Membership in The Institute of Electronics, Information and Communication Engineers (since April2014).
Membership in Association for Computing Machinery (2011).
Review Experience
1. IEEE Transactions on Autonomous Mental Development
2. Anual Meeting of the Cognitive Science Society
3. IEEE ICDL-EPIROB
4. International Workshop on Skill Science
5. Scientiﬃc Reports
6. Cognitive System Research
7. 認知科学
8. 認知心理学研究
9. 人工知能学会論文誌
10. 電子情報通信学会誌
11. 情報処理学会
12. 社会言語科学

Shohei Hidaka
Publication (updated on September 30, 2018)

Peer Reviewed Journal Articles
1. Fujinami, T. & Hidaka, H. (accepted). A representation of rhythmic motions, New Generation
Computing.
2. Hidaka S & Oizumi M (2018). Fast and exact search for the partition with minimal information
loss. PLoS ONE 13(9): e0201126.
3. 布山 美慕 & 日高 昇平 (2018). 読者の熱中に伴う仮想の変化：仮想の特徴づけとして. 認知科学, 25(2),188–199.
4. 鳥居拓馬 & 日 昇平 (2018). 利き手と逆の手の比較に基づく熟達技能への実験的アプローチ. 認知科
学. 25(1), 122-125.
5. 古川 康一, 諏訪 正樹, & 日高 昇平. (2017) 身体知研究を支える理論・方法論. 人工知能学会論文誌.,
32 (2), 222-228. (特集「身体知の発展」).
6. 日高 昇平 (2017). 最適化を超えた認知科学の新たなパラダイムに向けて：Marr の情報処理の三水準の再考. 認知科学., 24(1).
7. Buated, W., Lolekha, P., Hidaka, S., & Fujinami, T. (2016). Impact of Cognitive Loading on
Postural Control in Parkinson’s Disease with Freezing of Gait., Gerontology and Geriatric Medicine,
2, 1-8.
8. 日高昇平. (2016). 情報の伝達から理解へ. 人工知能学会論文誌., 31 (6).
9. 布山美慕 & 日高昇平. (2016). 読書時の身体情報による熱中度変化の記述., 認知科学, 23(2), 135–152.
10. Hidaka, S. (2016). Estimating the latent number of types in growing corpora with reduced costaccuracy trade-oﬀ., Journal of Child Language. 43, pp 107-134. (Published online: 24 February
2015)
11. 鳥居拓馬 & 日高昇平 (2015). 利己的な学習による相互協調：不確実な囚人のジレンマの分析. 認知科学, 22(3), 341-355. (Torii, T. & Hidaka, S. (2015). Mutual Cooperation Out of Greedy Learners:
Prisoner’s Dilemma Under Uncertainty., Cognitive Studies, 22(3) 341-355.)
12. Hidaka, S., Torii, T. & Masumi, A. (2015). Which types of learning make a simple game complex?,Complex Systems, 24(1), 49–74.
13. Imai, M., Miyazaki, M, Yeung, H., Hidaka, S., Kantartzis, K., Okada, H., & Kita, S. (2015). Sound
symbolism facilitates word learning in 14-month-olds., PLOS ONE, 10(2): e0116494.
14. Hidaka, S. (2014). General Type-Token Distribution., Biometrika, 101(4), 999–1002.
15. 日高 昇平 (2013). 人の多感覚コミュニケーションにおける情報ネットワークの可視化. 電気情報通信
学会誌, Vol. 96, No. 12, pp. 945-950.
16. Hidaka, S. (2013). A Computational Model Associating Learning Process, Word Attributes, andAge of Acquisition., PLOS ONE, 8(11): e76242.
17. Yurovsky, D., Hidaka, S., and Wu, R. (2012) Quantitative Linking Hypotheses for Infant Eye Movements., PLOS ONE, 7(10): e47419.
18. Hidaka, S. & Smith, L. B. (2011). Packing: A Geometric Analysis of Feature Selection and FastMapping in Children’s Category Formation., Cognitive System Research, 12 (1), 1-18.
19. Hidaka, S. & Smith, L. B. (2010). Acquisition of a Single Word to a Population of Words., Language
Learning and Development., 6 (3), 206-222.
20. Maouene, J. , Hidaka, S. & Smith, L. B. (2008). Body parts and early-learned verbs., Cognitive
Science, 32, 1200-1216.

21. 日高 昇平, 吉田 華子, & 齋木 潤. (2006) 発達研究固有の実験的制約を考慮した定量的分析方法〜バイ
リンガルの新奇語汎化課題に対する応用〜., 認知科学, 13, 484-487.
22. 日高 昇平 & 斎木 潤. (2005). 幼児の新奇語カテゴリ化のモデル研究., 認知科学, 12, 235-251. (InEnglish: Hidaka, S. & Saiki, S. (2005). A model study of infants novel word categorization.,
Cognitive Studies, 12, 235-251.)

Manuscripts under review/ in prepration
1. Hidaka, S. & Kashyap, N. (in preparation). Pointwise dimension estimation.
2. Hiaka, S. (in preparation). Recursive Markov Process.
3. 日高昇平. (in preparation). 情報概念の再構築 ―知識・理解・意味の創発を捉える新しい情報理解の理論に向けて.
4. Hidaka, S. & Kashyap, N. (in preparation). Dimensional clustering: a new perspective for machinelearning.
5. Hidaka, S. & Kashyap, N. (in preparation). Framing a class of frame problems.
6. Hidaka, S. & Fujinami, T. (in preparation) Characterizing Bodily Skills Through Dynamical Invariants.
7. Buated, W., Lolekha, P., Hidaka, S., Fujinami, T.. (under review). A Study of the Impact of
Cognitive Loading on Postural Control in Parkinson’s Disease with Freezing of Gait, Gerontology
and Geriatric Medicine.
8. Maouene, J., Hidaka, S., Uziel-Karl, S., Kuwabara, M., Maouene, M., & Sethuraman, N. (in preparation). Body parts and Early Japanese and Hebrew Verbs A cross-linguistic comparison in associations with English.
9. Hidaka, S. & Oizumi, M. (in preparation). Unbiased and asymptotically optimal estimator for thepartition with the minimal information loss.
10. Hidaka, S. & Saigo, H. (in preparation). Metaphor as Functor.
11. Hidaka, S., Torii, T., & kachergis, G. (in preparation). Child’s word learning is not individually nor
independently.
12. Hidaka, S. (in preparation). Hypergraphical information theory.
13. Hidaka, S. & Hira, R. (in preparation). Finding neuronal clusters by information partitioning.
14. Hidaka, S. (in preparation). Why should the fourth batter be a slugger?
15. Hidaka, S. (in preparation). Nash equilibriums of the iterated prisoner’s dilemma with the Markov
strategies.
16. Hidaka, S. (in preparation). Learning game players communicate.
17. Hidaka, S. (in preparation). Optimal strategies mirror game topologies.
18. Hidaka, S. (in preparation). Imitation as Dimensional Isomorphism.
19. Hidaka, S. (in preparation). Search for movements.

Book Chapters
1. Smith, L. B. Maouene, J. & Hidaka, S. (2007). The Body and Children’s Word Learning, In Plumert,
J. M., Spencer, J. P. (ed.) The Emerging Spatial Mind. Oxford University Press, Oxford, pp. 168–192.

Preprints
1. Hidaka, S. & Kashyap, N. (2018). Clustering by latent dimensions. eprint arXiv:1805.10759.
2. Hidaka, S. (2018). Polynomial algorithm for k-partition minimization of submodular system withstrong symmetry. eprint arXiv:1802.01914.
3. Hidaka, S. & Oizumi, M. (2017). Fast and exact search for the partition with minimal information
loss. eprint arXiv:1708.01444.
4. Hidaka, S. (2015). Recursive Markov Process., eprint arXiv:1509.00535.
5. Hidaka, S. & Kashyap, N. (2013). On the Estimation of Pointwise Dimension., eprint arXiv:1312.2298.
6. Hidaka, S. (2013). General Type Token Distribution., eprint arXiv:1305.0328.
7. Hidaka, S. (2012). Characterizing Multivariate Information Flows., eprint arXiv:1212.5449.

Peer Reviewed Conference Papers
1. Torii, T. & Hidaka, S. (2018). How can we help others?: a computational account for action completion. In Proceedings of The 40th Annual Meeting of the Cognitive Science Society (CogSci2018),
2572-2577.
2. Imai, M., Hidaka, S., Saji, N., & Ohba, M. (2018). Symbol grounding and system constructionin the color lexicon. In Proceedings of The 40th Annual Meeting of the Cognitive Science Society(CogSci2018), 1853-1858.
3. Hidaka, S., Torii, T., & Kachergis, G. (2017). Quantifying the impact of active choice in wordlearning. In Proceedings of The 39th Annual Meeting of the Cognitive Science Society (CogSci2017),
519–524.
4. Hidaka, S., Torii, T., & Kachergis, G. (2017). Leveraging mutual exclusivity for faster crosssituational word learning: A theoretical analysis. In Proceedings of The 39th Annual Meetingof the Cognitive Science Society (CogSci2017), 2205–2210.
5. Torii, T. & Hidaka, S. (2016). Toward a mechanistic account for imitation learning: an analysis ofpendulum swing-up. In Proceedings of the Third International Workshop on Skill Science.
6. Fuyama, M., & Hidaka, S.(2016). Context-dependent Processes and Engagement in Reading Literature. In Proceedings of The Thirty Fourth Annual Meeting of Cognitive Science Society (CogSci2016).
7. Fuyama, M. & Hidaka, S. (2015). Identifying Context-Dependent Modes of Reading. In Proceedingsof the Second International Workshop on Skill Science (SKL-2015).
8. Fujinami, T., Hidaka, S., & Kashyap, N. (2015). Evaluating Presence Based on Balance. The
International Symposium on Performance Science, Kyoto, Japan，02 - 05 September 2015.
9. Buated, W., Fujinami, T., Hidaka, S., Kashyap, N. (2015). Auditory cues on postural control in
Parkinson’s disease: A pilot study., The International Parkinson and Movement Disorder 2015, San
Diego, California, USA June 14-18, 2015.
10. Buated, W., Fujinami, T., Hidaka, S., Kashyap, N (2014). Balance Assessment for Parkinson.
The 10th International Congress on Non-Motor Dysfunctions in Parkinson’s Disease and Related
Disorders, Nice, France, December 4-7, 2014.
11. Hidaka, S. & Kashyap, N. (2014). The Generalist Approach to Framing Problems, In Proceedingsof The Third Asian Conference on Information Systems, 318-325. ((ACIS2014) held in Nha Trang,
Viet Nam, December 1st-3rd)
12. Hidaka, S., Torii, T. & Masumi, A. (2014). Tractable Infinite Order Markov Analysis for Iterated
Games with Learners, Joint 7th International Conference on Soft Computing and Intelligent Systems
and 15th International Symposium on Advanced Intelligent Systems, pp. 286–291. (2015 年度日本
知能情報ファジィ学会奨励賞)

13. Fuyama, M., Hidaka, S., & Suwa, M. (2014). The Continuous Measurement of Absorption in
Reading Based on the Time Series of Subjective Evaluation and Heart Rates. The JagiellonianRutgers Conference in Cognitive Science 2014 (CogSciJR14).
14. Miyazaki, M., Hidaka, S., Imai, M., Yeung, H. H., Kantartzis, K., Okada, H., & Kita, S. (2013).
The facilitatory role of sound symbolism in infant word learning. In Proceedings of The Thirty Fifth
Annual Meeting of Cognitive Science Society, 3080-3085.
15. Hidaka, S. & Fujinami, T. (2013). Topological Similarity of Motor Coordination in Rhythmic Movements. In Proceedings of The Thirty Fifth Annual Meeting of Cognitive Science Society, 2548-2553.
16. Hidaka, S. (2012) Identifying Kinematic Cues for Action Style Recognition. In Proceedings of The
Thirty Fourth Annual Meeting of Cognitive Science Society, 1679-1684.
17. Yurovsky, D., Hidaka, S., & Wu, R. (2012) Quantitative Linking Hypotheses for Infant Eye Movements, In Proceedings of The Thirty Fourth Annual Meeting of Cognitive Science Society, 1203-1208.
18. Nossal, N., Tsuchiyama, N., Hidaka, S., Iida, H. (2012). fNIRS Survey of Brain Function at theMoment of Winning, Game Programming Workshop 2012.
19. Suzuki, Y. & Hidaka., S. (2011). Estimating similarity judgment processes based on neural activities
measured by near-infrared spectroscopy (NIRS). (Also published in the book “Advances in Cognitive
Neurodynamics (III)”)
20. Hidaka S and Yu C (2011). Informational Coupling in Social Interaction as a Goodness of Communication. Front. Comput. Neurosci. Conference Abstract: IEEE ICDL-EPIROB 2011.
21. Hannagan T, Wu R, Hidaka S and Yu C (2011). A Computational Model for Cued Infant Learning.
Front. Comput. Neurosci. Conference Abstract: IEEE ICDL-EPIROB 2011.
22. Takahashi, K., Hidaka, S & Watanabe, K. (2010). Decoding Subjective Simultaneity from Neuromagnetic Signals, 17th International Conference on Biomagnetism.
23. Yurovsky, D., Hidaka, S., Yu, C., & Smith, L. B. (2010). A Generative Model of Eye, Movements in
Cross-Situational Learning. XVIIth Biennial International Conference on Infant Studies, Baltimore,
Maryland, March 10-14.
24. Yurovsky, D., Hidaka, S., Yu, C., & Smith, L. B. (2010) Liking Learning to Looking: Habituation
and Association in Infant Statistical Language Learning, In Proceedings of The Thirty Second Annual
Meeting of Cognitive Science Society, 1589-1594.
25. Hidaka, S., & Yu, C. (2010) Analyzing Multimodal Time Series as Dynamical Systems, 12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for MultimodalInteraction.
26. Hidaka, S., & Yu, C. (2010). Spatio-Temporal Symbolization of Multidimensional Time Series,
International Workshop on Spatial and Spatiotemporal Data Mining.
27. Yu, C., Smith, T.G., Hidaka, S., Scheutz, M., & Smith, L.B. (2010). A Data-Driven Paradigm toUnderstand Multimodal Communication in Human-Human and Human-Robot Interaction . In P.R.
Cohen, N.M. Adams, M.R. Berthold (Eds.) Advances in Intelligent Data Analysis IX, LNCS 6065
(pp. 232-244). Berlin/Heidelberg: Springer Verlag.
28. Hidaka, S., Maouene, J. & Smith, L. B. (2009). Diﬀerent Word Classes are Learned in Diﬀerent
Ways: Evidence from Vocabulary Growth. In Proceedings of International Cognitive Linguistics
Conference 11.
29. Hidaka, S. (2009). Diﬀerent Classes of Words are Learned in Diﬀerent Ways. In Proceedings of The
Thirty First Annual Meeting of Cognitive Science Society, oral presentation.
30. Maouene, J., Hidaka, S., & Smith, L. B. (2008). Body-Part Categories of Early-Learned Verbs: Different Granularities at Diﬀerent Points in Development In Proceedings of The Seventh International
Conference on Development and Learning.
31. Hidaka, S. & Smith, L. B. (2008). How Features Create Knowledge of Kinds. In Proceedings of The
Thirtyth Annual Meeting of Cognitive Science Society, pp. 1029–1035.

32. Hidaka, S. & Saiki, J. (2006). A solution to current limitations in the analysis of developmental
data. In The Fifteenth Biennial International Conference on Infant Studies.
33. Hidaka, S., Saiki, J., & Smith, L. B. (2006). Semantic packing as a core mechanism of category
coherence, fast mapping and basic level categories. In Proceedings of The Twenty Eighth Annual
Conference of Cognitive Society, pp. 1500–1505.
34. Maouene, J. , Hidaka, S. & Smith, L. B. , (2006). Body parts and the first 100 verbs., In Proceedingsof The Twenty Eighth Annual Conference of Cognitive Society, pp. 555–560.
35. Hidaka, S., Saiki, J., & Smith, L. B. (2006). Semantic packing: an account for category coherence.
In Proceedings of The Seventh International Conference on Cognitive Modelling, pp. 130–135.
36. Hidaka, S. & Saiki, J. (2006). Feature discovery in object individuation. In Proceedings of The Fifth
International Conference on Development and Learning.
37. Maouene, J. , Hidaka, S. & Smith, L. B. , (2006). Children and adults rely on body parts forearly-acquired verbs., In Proceedings of The Fifth International Conference on Development andLearning.
38. Hidaka, S. & Saiki, J. (2005). Prototype-specific learning for children’s vocabulary. In Proceedingsof The Fourth IEEE International Conference on Development and Learning, pp. 201.
39. Hidaka, S. & Saiki, J. (2004). A connectionist account of ontological boundary shifting. In N.R.
et al. Pal, editor, ICONIP 2004, Lecture Note in Computer Science 3316, pp. 22–25, Berlin,
Springer-Verlag.
40. Hidaka, S. and Saiki, J. (2004). A mechanism of ontological boundary shifting. In The Twenty Sixth
Annual Meeting of the Cognitive Science Society, pp. 565–570.

Invited Talks
1. 日高 昇平 (2018). 情報・学習・理解：機械学習から機械理解の定式化に向けて. M i2 ・JAIST 合同
シンポジウム「データ科学における予測と理解の両立を目指して − 分かるとは何か？ −」平成 30
年 5 月 21 日, JST 東京本部別館 1 階ホール.
2. Hidaka, S. (2016) Machine consciousness: a dream to build a strong AI., Japanese-Germa Frontiersof Science Symposium (JGFoS), Potsdam, Germany, October 6-9, 2016.
3. 日高 昇平 (2015). 身体動作から行為を切り出す方法論. 第 163 回ヒューマンコンピュータインタラク
ション研究発表会, 2015 年 5 月 14 日, 七尾市和倉温泉はまづる.
4. 日高 昇平 (2015). 身体動作の意味論に向けて：からだのことばを読み取る. 第 46 回ヴァーバル・ノン
ヴァーバル・コミュニケーション研究会, 2015 年 2 月 28 日, 国立情報学研究所.
5. 日高 昇平 (2014). 最適化ではない計算論：統計的モデリングと非線形力学的解析法の融合., Young
Perceptionists’ Seminar・若手会ジョイントセミナー, 2014 年 9 月 5 日, 休暇村志賀島（福岡県福岡市東区）.
6. 日高昇平 (2013). 模倣の基礎理論の構築およびシミュレーションによる実証., 第１４回人工知能研究
成果発表会. 2013 年 9 月 18 日, 今池ガスビル.
7. Hidaka, S. (2013). Statistical Modeling of Eye Movements in Cognitive Developmental Studies . In
Symposium ”Probabilistic Principles of Brain Computation”, Neuro2013. (日高 昇平 (2013). 認知
発達研究における注視行動の統計的モデリング., 神経回路学会シンポジウム「脳と確率」(2013 年 6 月
20 日〜23 日, 京都国際会館)
8. Hidaka, S. (2012). Word Learning In Social Interaction. In Cognitive Science Spring Seminars(University of Malta, March, 26th, 2012).
9. Hidaka, S. (2012). Decoding emotional contexts in bodily actions., Lecture for Master in the Scienceof Performative Creativity (University of Malta, March, 29th, 2012).

10. Shohei Hidaka (2012). Characterizing Attention and Learning from Infant Eye Movements., In theworkshop ”Gaze Bias Learning II”, Linking neuroscience, computational modeling, and cognitivedevelopment., Tamagawa University.
11. 日高 昇平 & 西田 豊 (2012). 統計的モデルの考え方：確率分布から多変量解析まで, 日本認知科学会・
対話と学習研究会・第 46 回研究会.
12. Hidaka, S. (2012). Toward a computational model of creativity: Novel hypothesis generation fromstructural knowledge. Seventh International Conference on Knowledge, Information and Creativity
Support Systems.
13. 日高昇平 (2011). 身体動作に内在する状況性への情報理論的アプローチ, 第 32 回社会的知能発生学研究会, 2011 年 12 月 22-23 日, リッチモンドホテルプレミア仙台.

Reports/ Reviews/ Invited
1. 日高 昇平, Wannipat Buated, & 藤波 努 (2016). 重心運動を指標としたパーキンソン病の潜在リスクの推定., 第 22 回身体知研究会予稿集 (SIG-SKL), 26-29.
2. 日高 昇平 (2015). 身体動作の意味論に向けて., 第 2 回間合い研究会 (間合い, SIG Maai, Vol. 2015,
No. 1, 26-31).
3. 布山 美慕，日高 昇平，諏訪 正樹. (2015). ページ送りの時間間隔に基づく読書の認知処理の分析. 知識共創第 5 号.
4. 日高 昇平 (2013). データから知識へ：多変量情報流による潜在的機構の推定., 知識共創フォーラム(知識共創第 3 号, III7-1-III7-10).
5. 日高 昇平 (2013). 力学的不変量仮説： 運動制御の最適化理論の上位原理として., 第 15 回身体知研究会予稿集, 9-15. (Dynamical Invariance Hypothesis: As a Superordinate Principle Upon Motor
Control Optimality Theory., SIG-SKL-15, 9-15.)
6. 日高 昇平 & 西田 豊 (2012). 統計的モデルの考え方：確率分布から多変量解析まで, 学習と対話 Vol.
2012, No.1, 21-26 (日本認知科学会・対話と学習研究会・第 46 回研究会).
7. Tanaka, A., Takezawa, M., Nakamura, K., Hayashi, Y. , Hidaka, S. & Honda, H. (2009). Reports of the 31st Annual Conference of the Cognitive Science Society and Cognitive Science in the
Netherlands, Cognitive Studies Vol. 16, No. 4, pp.532-540.

Miscellaneous
1. 幼児の語彙力統計学で測定, 北國新聞 (2014 年 9 月 11 日, 32 面掲載)
Research Grants
1. JSPS KAKENHI Grant-in-Aid for Young Scientists (A) 16H05860, as PI (平成 28 年度科学研究費補助金若手研究 A, 2016-2018 年度, 総額 18,360,000 円, 代表, 研究課題「力学系の不変量による身体運動の分節化・認識・生成理論の構築」).
2. JSPS KAKENHI Grant-in-Aid for Scientific Research on Innovative Areas 16H01609, as PI (平成28 年度科学研究費補助金新学術領域研究（研究領域提案型）, 2016-2018 年度, 総額 5,060,000 円, 代表, 研究課題「神経ネットワークの高次情報解析に基づく非線形動力学モデルの構築」).
3. JSPS KAKENHI Grant-in-Aid for Scientific Research B (Generative Research Fields) 15KT0013, asPI (平成 27 年度科学研究費補助金基盤研究 B (特設分野研究), 2015-2017 年度, 総額 15,900,000 円, 代表, 研究課題「非線形時系列解析による神経結合推定法の開発」).
4. JSPS KAKENHI Grant-in-Aid for Challenging Exploratory Research 25560297, as PI (科学研究費補助金挑戦的萌芽研究, 2013-2014 年度, 総額 3,900,000JPY, 代表, 研究課題「運動の位相的類似による模倣の基礎理論の構築」).

5. JSPS KAKENHI Grant-in-Aid for Scientific Research B (General) 23300099, as PI (科学研究費補助
金基盤研究 B, 2011-2014 年度, 総額 8,060,000 円, 代表, 研究課題「行動情報解析による意味知識ネッ
トワークの発達過程の解明」).
6. 2012 年度研究者支援創造性研究奨励賞 (NeuroCreative Lab, 2013 年度, 総額 1,000,000 円, 代表).
7. JAIST Grant for Advanced Research Base (平成 23 年度
500,000 円, 分担).

先端研究拠点形成支援, 2011-2012 年,

8. JSPS KAKENHI Grant-in-Aid for Scientific Research Activity Start-up 22800028, as PI (科学研究費補助金 研究活動スタート支援, 2011-2012 年度, 総額 2,782,000 円, 代表, 研究課題「注視行動の非線
形予測モデルによる認知発達過程の理解」).
9. Artificial Intelligence Research Promotion Foundation 22AI 161-9, as PI (平成 23 年度人工知能研究助成金, 22AI 第 161 号-9, 財団法人人工知能研究振興財団, 2011-2012 年度, 総額 500,000 円, 代表).
10. KEKENHI Grant-in-Aid for JSPS Fellows 06J02935, as PI (科学研究費補助金特別研究員奨励費,
2006-2007 年度, 総額 1,900,000 円, 代表, 研究課題「視覚特徴の階層性がもたらす物体のカテゴリ化バイアス」).
Honors and Awards
1. 第五回野島久雄賞 (日本認知科学会, 2017 年 9 月 13 日)
2. 論文誌「認知科学」奨励論文賞 (日本認知科学会, 2017 年 9 月 14 日; 布山美慕氏との共著論文に対して). 受賞論文: 布山 美慕 & 日高 昇平 (2016). 読書時の身体情報による熱中度変化の記述. 認知科学,
23(2), 135–152.
3. 日本認知科学第 34 回大会発表賞 (日本認知科学会, 2017 年 12 月 16 日; 鳥居拓馬氏との共同研究の発表に対して). 受賞発表: 鳥居 拓馬 & 日
昇平 (2017). 利き手と逆の手の比較に基づく熟達技能への実験的アプローチ. 日本認知科学会第 34 回大会論文集. (O1-3).
4. 第 5 回知識共創フォーラム共創賞受賞 (筆頭著者：布山 美慕).(2016 年 1 月)
5. 2015 年度日本知能情報ファジィ学会奨励賞. (2015 年 9 月)
6. 第 5 回知識共創フォーラム萌芽研究賞受賞 (筆頭著者：布山 美慕).(2015 年 3 月)
7. 2014 年度 (第 28 回）人工知能学会全国大会優秀賞（JSAI Annual Conference Award）(筆頭著者：布山 美慕).
8. 2012 年度研究者支援創造性研究奨励賞 (NeuroCreative Lab, 2012).
9. British Psychological Society International Collaboration Award (For our collaborative work with
Ratchel Wu and Daniel Yurovsky, British Psychological Society, 2010).
10. Travel Grant for International Conference, Kyoto University Foundation, 2006.
11. Travel Grant for Short term International Research, Kyoto University, 2006.
12. Travel Grant for Short term International Research, Kyoto University, 2005.
13. Travel Grant from the Japan Cognitive Science Society, 2009 (Reported in Cognitive Studies Vol.
16 (2009) , No. 4 pp.532-540).
14. Research grand for young scientists, Kyoto University, 2005.
15. Outstanding Paper Award, 22th Annual Conference of the Japanese Cognive Science Society, 2005
(第 22 回認知科学会発表賞, 日本認知科学会, 2005 年 7 月).
Computer Skills
Expert: Matlab
Intermediate: R, Perl, LATEX, HTML, ActionScript, C, Python, Scala
Basic: C++ , Ruby, SQL, Mathematica, Linux, SPSSComputatioinal Modeling Skill
Datamining/Machine Learning techniques for a large scale cognitive and psychological database.
Applied Statistics, Complex Network, Neural Networks, Corpus Linguistics, Bayesian Modelling,
Nonliear Time Series Analysis, and Game Theory.
Languages
Japanese (mother tongue)
English (fluent)
Other Skills
The game of Go (Baduk in Korean, Weiqi in Chinese): Amateur expert level (6 dan in Japaneseranking, won 4th rank in the Ishikawa preliminary of the World Amateur Championship 2015),
Shogi (Japanese Chess): Amateur intermediate grade (1 dan in Japanese ranking).
Judo 1 dan (black belt).