YUWEI SUN

ywsun@g.ecc.u-tokyo.ac.jp ǀ +81-8081165839
7 Chome-3-1 Hongo, Bunkyo City, Tokyo 113-8654, JapanEDUCATIONThe University of TokyoTokyo, Japan
Ph.D., Information Science and Technology (Hons.) GPA: 4.0/4.004-2021 ~ 03-2024
Minor: International Graduate Program of Innovation for Intelligent World
Thesis: Localized Learning and Generalization in Artificial Neural Networks with Properties of theGlobal Workspace (Best thesis award)
M.S., Information and Communication Engineering (Hons.) GPA: 3.84/4.0
04-2019 ~ 03-2021
Honor: Department Chair’s Award
Thesis: Network Intrusion Detection Based on Distributed Trustworthy Artificial Intelligence
Research Focus: Decentralized Neural Networks, AI Security and Privacy
Post-Graduate Research Program, Graduate School of Information Science and Technology
Research Focus: Decentralized Neural Networks

10-2018 ~ 03-2019

North China Electric Power University
B.S., Computer Science and Technology (Hons.)
Thesis: Attacks on Deep Learning Systems Based on Generative Adversarial Networks
Research Focus: Computer Vision

Beijing, China
09-2014 ~ 08-2018

EXCHANGE EXPERIENCES
Massachusetts Institute of Technology
Fellow of the Advanced Study Program, Graduate School of Engineering
Courses: Distributed neural circuits, Underactuated robotics, Blockchain

Cambridge, MA, US02-2020 ~ 05-2020

University of Pennsylvania
Visiting Student

Philadelphia, PA, US
08-2019 ~ 10-2019

Waseda University
Visiting Student

Tokyo, Japan
10-2016 ~ 08-2017

EMPLOYMENT
Araya
Senior Researcher- Research on Global Workspace Theory and machine consciousness

Tokyo, Japan04-2024 ~ Present

Research Assistant
04-2023 ~ 03-2024- Research neuroscience-inspired attention and long-term memory mechanism in Transformers
RIKEN Center for Advanced Intelligence ProjectTokyo, Japan
Visiting Scientist, AI Security and Privacy Team
04-2024 ~ Present- Research on mitigating hallucination in Transformers based on weak-to-strong generalization
PhD Student Researcher, AI Security and Privacy Team- Perform research on localized learning and multimodal models

04-2021 ~ 03-2024

The University of Tokyo
Research Fellow DC, Japan Society for the Promotion of ScienceTokyo, Japan04-2022~ 03-2024

Research Assistant, Graduate School of Information Science and Technology

04-2020 ~ 03-2022

United Nations University
Consultant, Computing Centre- Researched multi-source domain adaptation and its application in vision and text data

Tokyo, Japan05-2021 ~ 06-2022

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Research Intern- Performed research on privacy-preserving decentralized machine learning

06-2020 ~ 12-2020

RESEARCH GRANTS
Previous- Microsoft Research Asia Collaborative Research Program (D-CORE 2023), JPY1270k, 2023-2024- Japan Society for the Promotion of Science, Grant-in-Aid for JSPS Fellows, JPY1700k, 2022-2024- Japan Science and Technology Agency, SPRING GX program, JPY340k, 2021-2022
SELECTED PUBLICATIONSJournals• Yuwei Sun, Hideya Ochiai, and Jun Sakuma. Attacking Distance-aware Attack: A Semi-targeted Poisoning
Attack on Federated Learning. IEEE Transactions on Artificial Intelligence. 2023.
• Yuwei Sun and Hideya Ochiai. Homogeneous Learning: Self-Attention Decentralized Deep Learning. IEEEAccess, Vol.10, pp.7695-7703. 2022.
•Yuwei Sun, Hideya Ochiai, and Hiroshi Esaki. Decentralized Deep Learning for Multi-Access Edge
Computing: A Survey on Communication Efficiency and Trustworthiness. IEEE Transactions on Artificial
Intelligence, Vol.3, No.6, pp.963-972. 2022.

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Yuwei Sun, Hideya Ochiai, and Hiroshi Esaki. Adaptive Intrusion Detection in the Networking ofLarge-Scale LANs with Segmented Federated Learning. IEEE Open Journal of the Communications Society,Vol.2, pp.102-112. 2020.

Conferences• Yuwei Sun and Hideya Ochiai. Bidirectional Contrastive Split Learning for Visual Question Answering. AAAI.
2024.
•Yuwei Sun, Hideya Ochiai, Zhirong Wu, Stephen Lin, Ryota Kanai. Associative Transformer is a Sparse
Representation Learner. NeurIPS Workshop on Associative Memory and Hopfield Networks. 2023.

•Yuwei Sun. Meta Learning in Decentralized Neural Networks: Towards More General AI. AAAI DoctoralConsortium. 2023.
Yuwei Sun and Hideya Ochiai. UniCon: Unidirectional Split Learning with Contrastive Loss for VisualQuestion Answering. NeurIPS Workshop on Self-Supervised Learning. 2022.

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Yuwei Sun, Ng Chong, and Hideya Ochiai. Feature Distribution Matching for Federated Domain
Generalization. Asian Conference on Machine Learning (ACML). 2022.

•Yuwei Sun, Hideya Ochiai, and Jun Sakuma. Semi-Targeted Model Poisoning Attack on Federated Learningvia Backward Error Analysis. IEEE International Joint Conference on Neural Networks (IJCNN). 2022.

•Yuwei Sun, Hideya Ochiai, and Hiroshi Esaki. Intrusion Detection with Segmented Federated Learning forLarge-Scale Multiple LANs. IEEE International Joint Conference on Neural Networks (IJCNN). 2020.

HONORS AND AWARDS- Best PhD Thesis Award, The University of Tokyo, 2024
- WBAI Incentive Award, Whole Brain Architecture Initiative, 2023
- AAAI Student Scholarship, 2023- Department Chair’s Award, The University of Tokyo, 2021
- Heiwa Nakajima Foundation Scholarship, 2021
- Scholarship, The University of Tokyo, 2019
- Scholarship, North China Electric Power University, 2016
- Successful Participant, COMAP Mathematical Contest in Modeling, 2015
SKILLS
Programming: Python (Advanced), PyTorch (Advanced), Tensorflow (Advanced), OpenCV (Advanced), Linuxcommands (Intermediate), Git (Intermediate), Docker (Intermediate), SQL (Intermediate), HTML (Intermediate),
JavaScript (Elementary), C++ (Elementary), Java (Elementary)
AI Research Computer: RAIDEN by Fujitsu in RIKEN Center for Advanced Intelligence Project
Languages: Chinese (native), English (TOEFL IBT 101/120), Japanese (JLPT N1 169/180)
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OTHER ACTIVITIESTalks• April 2024, “Localized Learning and Generalization in Artificial Neural Networks with Properties of the GlobalWorkspace”, an invited talk at International Research Center for Neurointelligence (IRCN), the University ofTokyo.
• August 2023, “Localized Learning Through the Lens of Global Workspace Theory”, a talk at the Consciousness
Research Network (CoRN)• April 2023, “Meta Learning in Decentralized Neural Networks Through the Lens of Global Workspace
Theory”, an invited talk at MBZUAI and RIKEN-AIP Joint Workshop on Intelligent Systems• Feb 2023, “Meta Learning in Decentralized Neural Networks Through the Lens of Global Workspace Theory”,
an invited talk at Victoria University of Wellington• Nov 2022, “Meta Learning and Modularity Towards Systematic Generalization”, an inner group talk at the MIT
Department of Brain and Cognitive Sciences• Mar 2021, “Segmented Federated Learning”, an invited talk at Workshop on Algorithm and Big Data,
Transdisciplinary Information Sciences conferences
Academic Services• Reviewer: IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on ArtificialIntelligence, Neural Networks, Engineering Applications of Artificial Intelligence, ACM Multimedia, NeurIPS,CVPR, ICML, IJCNN, ACML, AISTATS••Volunteer for NeurIPS 2021, ICLR 2023
Organizer for the NeuroAI Social at NeurIPS 2023

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