Biography
Jiawei Zhang is currently a postdoctoral scholar in the Laboratory for Information & Decision Systems (LIDS) at MIT, working with Prof. Asuman Ozdaglar and Prof. Saurabh Amin. He obtained the Ph.D. degree in Computer and Information Engineering from the Chinese University of Hong Kong (CUHK), with an advisory of Prof. Zhi-Quan (Tom) Luo. Previously, he obtained the B.Sc. in Mathematics (Hua Loo-Keng Talent Program) from the University of Science and Technology of China.
Interests
- Nonlinear and convex optimization: theory and algorithms
- Learning algorithms: robustness and generalization
- Data-driven decision-making under uncertainty
- New computational models for AI-driven platforms, sustainable energy systems, and signal processing
Education
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Ph.D. in Computer and Information Engineering
The Chinese University of Hong Kong (CUHK)
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B.Sc. in Mathematics (Hua Loo-Keng Talent Program)
University of Science and Technology of China (USTC)
Recent Publications
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(2023).
Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation.
Proceedings of the 40th International Conference on Machine Learning (ICML 2023).
(2023).
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach.
Proceedings of the 40th International Conference on Machine Learning (ICML 2023).
(2022).
On the Iteration Complexity of Smoothed Proximal ALM for Nonconvex Optimization Problem with Convex Constraints.
arXiv preprint arXiv:2207.06304.
(2022).
What is a Good Metric to Study Generalization of Minimax Learners?.
Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
(2022).
A Global Dual Error Bound and Its Application to the Analysis of Linearly Constrained Nonconvex Optimization.
SIAM Journal on Optimization.