Jiawei Zhang

Jiawei Zhang

Assistant professor in CS @ UW-Madison

University of Wisconsin–Madison

Biography

Jiawei Zhang is an assistant professor in the Department of Computer Sciences at University of Wisconsin–Madison. Previously, he was a postdoctoral fellow supported by The MIT Postdoctoral Fellowship For Engineering Excellence 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, Shenzhen, with an advisory of Prof. Zhi-Quan (Tom) Luo, and was honored with the Presidential Award for Outstanding Doctoral Students. 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
  • Optimization, generalization, and robustness of machine learning, reinforcement learning, generative models (including diffusion models, large models, foundation models)
  • Data-driven decision-making under uncertainty
  • New computational models for AI-driven platforms, sustainable energy systems, and signal processing
Education

  • Ph.D. in Computer and Information Engineering

    The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen)

  • B.Sc. in Mathematics (Hua Loo-Keng Talent Program)

    University of Science and Technology of China (USTC)

News

Slides on our recent works on optimal first-order algorithms for stochastic constrained optimization, theoretical analysis of GRPO from the adaptive gradient descent perspective, and lossless, efficient inference for diffusion language models, have been uploaded.
Congratulations to my first undergraduate intern, Ruichuan, for getting a Spotlight at ICML with his very first submission! Many thanks to my collaborator Ahmet Alacaoglu for co-supervising him with me.
Our paper "Addressing misspecification in contextual optimization", arXiv preprint arXiv:2409.10479, has been accepted by ICML 2025.
Our paper "Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints", arXiv preprint arXiv:2504.07607, has been accepted by ICML 2025.
I will join the Department of Computer Sciences at the University of Wisconsin–Madison as a tenure-track professor.

Research Topics

  • Efficient, scalable, generalizable, and robust optimization algorithms for large-scale optimization problems, including LLM training, constrained optimization, and bilevel optimization.

  • Fundamental theories and algorithms for generative models, including LLMs and diffusion models, focusing on efficient and reliable training and inference.

  • Optimization and decision-making for engineering applications, including energy systems and communication systems.

Prospective Students

I am looking for students interested in the research areas mentioned above or related topics about optimization, machine learning and their applications to science and engineering starting in 2025. They should have either a strong background in math and good coding skills, or a strong coding ability and adept theoretical insights. Students with backgrounds in mathematics, statistics, computer science, electronic engineering, and other related fields are welcome to apply.

Recent Publications

Jiawei Zhang (2025). Efficient Optimization, Post Training and Inference.

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Shutong Wu, Jiawei Zhang (2025). Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models. arXiv preprint arXiv:2510.00294.

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Kihyun Kim, Jiawei Zhang, Asuman Ozdaglar, Pablo A Parrilo (2025). Population-Proportional Preference Learning from Human Feedback: An Axiomatic Approach. arXiv preprint arXiv:2506.05619.

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Wei Shen, Zhang Yaxiang, Minhui Huang, Mengfan Xu, Jiawei Zhang, Cong Shen (2025). MLorc: Momentum Low-rank Compression for Large Language Model Adaptation . arXiv preprint arXiv:2506.01897.

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Wei Shen, Ruichuan Huang, Minhui Huang, Cong Shen, Jiawei Zhang (2025). On the convergence analysis of muon. arXiv preprint arXiv:2505.23737.

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Preprint Papers

Shutong Wu, Jiawei Zhang (2025). Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models. arXiv preprint arXiv:2510.00294.

Cite

Kihyun Kim, Jiawei Zhang, Asuman Ozdaglar, Pablo A Parrilo (2025). Population-Proportional Preference Learning from Human Feedback: An Axiomatic Approach. arXiv preprint arXiv:2506.05619.

Cite

Wei Shen, Zhang Yaxiang, Minhui Huang, Mengfan Xu, Jiawei Zhang, Cong Shen (2025). MLorc: Momentum Low-rank Compression for Large Language Model Adaptation . arXiv preprint arXiv:2506.01897.

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Wei Shen, Ruichuan Huang, Minhui Huang, Cong Shen, Jiawei Zhang (2025). On the convergence analysis of muon. arXiv preprint arXiv:2505.23737.

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Jiawei Zhang, Wenqiang Pu, Zhi-Quan Luo (2022). On the Iteration Complexity of Smoothed Proximal ALM for Nonconvex Optimization Problem with Convex Constraints. arXiv preprint arXiv:2207.06304.

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Teaching Experience

Award

Outstanding Teaching Assistant granted by School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China

Awards

The MIT Postdoctoral Fellowship For Engineering Excellence, Massachusetts Institute of Technology, 2023
Presidential Award for Outstanding Doctoral Students, The Chinese University of Hong Kong, Shenzhen, 2021
PhD Fellowship, Shenzhen Research Institute of Big Data, 2020-2021

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