Projects per year
Personal profile
Chinese Name
Biography
Bo Han is currently an Assistant Professor of Computer Science and a Director of Trustworthy Machine Learning and Reasoning Group at Hong Kong Baptist University, and a BAIHO Visiting Scientist at RIKEN Center for Advanced Intelligence Project (RIKEN AIP). He was a Visiting Faculty Researcher at Microsoft Research (2022) and a Postdoc Fellow at RIKEN AIP (2019-2020). He received his Ph.D. degree in Computer Science from University of Technology Sydney (2015-2019). During 2018-2019, he was a Research Intern with the AI Residency Program at RIKEN AIP, working on trustworthy representation learning (e.g., Co-teaching and Masking). He also works on causal representation learning (e.g., CausalAdv and CausalNL). He has co-authored a machine learning monograph, including Machine Learning with Noisy Labels (MIT Press). He has served as area chairs of NeurIPS, ICML and ICLR, senior program committees of AAAI, IJCAI and KDD, and program committees of AISTATS, UAI and CLeaR. He has also served as action (associate) editors of Transactions on Machine Learning Research, Neural Networks and IEEE Transactions on Neural Networks and Learning Systems, and editorial board members of Journal of Machine Learning Research and Machine Learning Journal. He received the RIKEN BAIHO Award (2019), RGC Early CAREER Scheme (2020), MSRA StarTrack Program (2021) and Tencent AI Focused Research Award (2022).
Research Interests
- Weakly Supervised Representation Learning
- Security, Privacy and Robustness in Machine Learning
- Automated, Federated and Graph Machine Learning
- Interdisciplinary Problems (e.g., Healthcare Analytics and Drug Discovery)
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
PhD, University of Technology Sydney
Feb 2015 → Feb 2019
Fingerprint
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Collaborations and top research areas from the last five years
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分布外数据下的可信图表征学习研究 Trustworthy Graph Representation Learning under Out-of-distribution Data
HAN, B. (PI), ZHANG, Y. (CoI), WANG, Q. (CoI), ZHU, J. (CoI), ZHOU, Z. (CoI), JIANG, X. (CoI), TIAN, H. (CoI) & PENG, X. (CoI)
1/01/24 → 31/12/26
Project: Research project
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The Research on Trustworthy Federated Learning with Application to PaddlePaddle
HAN, B. (PI)
31/10/23 → …
Project: Research project
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New Directions in Trustworthy Machine Learning
HAN, B. (PI)
1/12/23 → 30/11/24
Project: Research project
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New Directions in Trustworthy Machine Learning
HAN, B. (PI)
1/12/22 → 30/11/23
Project: Research project
Research Output
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W-DOE: Wasserstein Distribution-agnostic Outlier Exposure
Wang, Q., Han, B., Liu, Y., Gong, C., Liu, T. & Liu, J., 17 Jan 2025, (E-pub ahead of print) In: IEEE Transactions on Pattern Analysis and Machine Intelligence. p. 1-14 14 p., 10844561.Research output: Contribution to journal › Journal article › peer-review
Open Access -
Accurate Forgetting for Heterogeneous Federated Continual Learning
Wuerkaixi, A., Cui, S., Zhang, J., Yan, K., Han, B., Niu, G., Fang, L., Zhang, C. & Sugiyama, M., May 2024, Proceedings of the Twelfth International Conference on Learning Representations, ICLR 2024. International Conference on Learning Representations, p. 1-19 19 p. (Proceedings of the International Conference on Learning Representations, ICLR).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access1 Citation (Scopus) -
A Sober Look at the Robustness of CLIPs to Spurious Features
Wang, Q., Lin, Y., Chen, Y., Schmidt, L., Han, B. & Zhang, T., Dec 2024, 38th Conference on Neural Information Processing Systems, NeurIPS 2024. Neural Information Processing Systems Foundation, p. 1-40 40 p. (Advances in Neural Information Processing Systems; vol. 37)(NeurIPS Proceedings).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
A Time-consistency Curriculum for Learning from Instance-dependent Noisy Labels
Wu, S., Zhou, T., Du, Y., Yu, J., Han, B. & Liu, T., Jul 2024, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 46, 7, p. 4830-4842 13 p.Research output: Contribution to journal › Journal article › peer-review
1 Citation (Scopus) -
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-Noise Learning
Zhang, J., Song, B., Wang, H., Han, B., Liu, T., Liu, L. & Sugiyama, M., 1 Jun 2024, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 46, 6, p. 4398-4409 12 p., 10404058.Research output: Contribution to journal › Journal article › peer-review
6 Citations (Scopus)
Prizes
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Tencent Rhino-Bird Focused Research Program for Machine Learning Research
HAN, B. (Recipient), 25 Apr 2022
Prize: Other distinction
Activities
- 7 Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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IEEE Transactions on Pattern Analysis and Machine Intelligence (Journal)
HAN, B. (Associate editor)
Jun 2024 → …Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Journal of Artificial Intelligence Research (Journal)
HAN, B. (Associate editor)
Jul 2023Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Machine Learning (Journal)
HAN, B. (Associate editor)
Aug 2023Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Transactions on Machine Learning Research (Journal)
HAN, B. (Associate editor)
Mar 2022Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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IEEE Transactions on Neural Networks and Learning Systems (Journal)
HAN, B. (Associate editor)
Aug 2022Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)