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)
Education/Academic qualification
PhD, University of Technology Sydney
Feb 2015 → Feb 2019
Fingerprint
- 1 Similar Scholars
Collaborations and top research areas from the last five years
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The Research on Trustworthy Federated Learning with Application to PaddlePaddle
31/10/23 → …
Project: Research project
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Trustworthy Deep Learning for Large-scale Online Advertisement
21/06/22 → 21/06/23
Project: Research project
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Class-Wise Denoising for Robust Learning under Label Noise
Gong, C., Ding, Y., Han, B., Niu, G., Yang, J., You, J. J., Tao, D. & Sugiyama, M., 1 Mar 2023, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 45, 3, p. 2835-2848 14 p.Research output: Contribution to journal › Journal article › peer-review
3 Citations (Scopus) -
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
Zhu, J., Yao, J., Liu, T., Yao, Q., Xu, J. & Han, B., 2 Feb 2023, Proceedings of The Eleventh International Conference on Learning Representations, ICLR 2023. International Conference on Learning Representations, p. 1-34 34 p.Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
Detecting Out-of-distribution Data through In-distribution Class Prior
Jiang, X., Liu, F., Fang, Z., Chen, H., Liu, T., Zheng, F. & Han, B., Jul 2023, Proceedings of the 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, 22 p. (Proceedings of Machine Learning Research; vol. 202).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation
Dong, R., Liu, F., Chi, H., Liu, T., Gong, M., Niu, G., Sugiyama, M. & Han, B., Jul 2023, Proceedings of 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, p. 8260-8275 16 p. (Proceedings of Machine Learning Research; vol. 202).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access -
Exploring Model Dynamics for Accumulative Poisoning Discovery
Zhu, J., Guo, X., Yao, J., Du, C., He, L., Yuan, S., Liu, T., Wang, L. & Han, B., Jul 2023, Proceedings of the 40th International Conference on Machine Learning, ICML 2023. Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S. & Scarlett, J. (eds.). ML Research Press, Vol. 202. p. 42983-43004 22 p. (Proceedings of Machine Learning Research; vol. 202).Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review
Open Access
Prizes
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Tencent Rhino-Bird Focused Research Program for Machine Learning Research
HAN, Bo (Recipient), 25 Apr 2022
Prize: Other distinction
Activities
- 6 Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Machine Learning (Journal)
Bo HAN (Associate editor)
Aug 2023Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Journal of Artificial Intelligence Research (Journal)
Bo HAN (Associate editor)
Jul 2023Activity: 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)
Bo HAN (Associate editor)
Aug 2022Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Transactions on Machine Learning Research (Journal)
Bo HAN (Associate editor)
Mar 2022Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)
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Neural Networks (Journal)
Bo HAN (Associate editor)
Sept 2021Activity: Publication peer-review/editorial work › Editor/reviewer for publications (incl. CDCF T61 Journal Editor)