I am an assistant professor in the School of Computing and Data Science at The University of Hong Kong and The HKU Musketeers Foundation Institute of Data Science. I am generally interested in machine learning, stochastic optimization, and graph learning, with a special focus on the theoretical/empirical understanding (or Physics) of deep learning (especially foundation models). I am also particularlly interested in devloping the AI/ML methods for practical problems in other area, such as signal processing, intelligent transportation, and math problems.

Previously, I obtained my Ph.D. in the Computer Science department at the University of California, Los Angeles (UCLA), supervised by Prof. Quanquan Gu. I obtained my master degree in electrical engineering and bachelor degree in applied physics, both in Unversity of Science and Technology of China (USTC).

News

• Multiple openings for PhD, Postdoc, and RA. Please drop me an email with your CV and transcript (optional) if you are interesed in joining my research group. For interested PhD candidates in 2025, please submit your application in https://i.cs.hku.hk/~gradappl/index.html and inform me via email.

• [2025-09] Seven papers are accepted to NeurIPS 2025.

• [2025-09] Welcoming new PhD students Yufei Zhao, Xuan Tang, Bingqing Jiang, Dechen Zhang, and Xu Wang.

• [2025-08] One paper is accepted to EMNLP 2025.

• [2025-05] One paper is accepted to ACL 2025.

• [2025-05] Three papers are accepted to ICML 2025.

• [2025-03] One paper is accepted to CVPR 2025.

• [2025-01] Our school is lanching summer research program (see our website with full funding support. Please feel free to apply and send me email if you want to work with me.

• [2025-01] Four papers are accepted to ICLR 2025.

• [2024-09] Five papers are accepted to NeurIPS 2024.

• [2024-06] One paper on faster diffusion inference/sampling is accepted to SPIGM @ ICML workshop as an oral presentation and wins the best paper award!

• [2024-05] One paper on faster non-log-concave sampling is accepted to COLT 2024.

• [2024-05] Four papers on handling spurious correlation via better group classifier, transformer expressive power with varying layers, faster rate of stochastic proximal sampler, and benign overfitting for XOR data are accepted to ICML 2024.

• [2024-04] One paper on continual learning for GNN is accepted to CoLLAs 2024.

• [2024-01] Three papers on SGD with large learning rate, scalable training of dynamic GNN, and finite sample in-context learning are accepted to ICLR 2024.

• [2023-05] Our paper on the implicit bias of batch normalization is accepted to COLT 2023.

• [2023-03] Two manuscripts on explaning the advantages of Mixup and Gradient Regularization in training neural networks are online.

• [2023-03] I will serve as the Area Chair in NeurIPS 2023.

• [2023-01] Our paper on the generalization separation between Adam and GD has been accepted by ICLR 2023.

• [2022-09] Two papers accepted by NeurIPS 2022. The first paper studies the generalization of multi-pass SGD for over-parameterized least squres; the second paper demonstrates the power and limitation of pretraining-finetunning for linear regression with distribution shift.

• [2022-08] Dr Difan Zou just joined HKU CS as an assistant professor.