Mingze Wang

Mingze Wang 

Mingze Wang (王铭泽)
Ph.D. Candidate

School of Mathematical Sciences
Peking University

210, Jingyuan Building #6 (静园六院), Peking University
210, Building #20 (20楼), Peking University
Beijing, China, 100084

Email: mingzewang [at] stu [dot] pku [dot] edu [dot] cn

[Google Scholar]     [CV]

About me

I am a fourth-year Ph.D candidate in Computational Mathematics, School of Mathematical Sciences, Peking University (2021-Present). I am very fortunate to be advised by Prof. Weinan E. Prior to that, I received my B.S. degree in Pure and Applied Mathematics (ranking 1/111 for the first three years during my undergraduate study) from School of Mathematical Sciences, Zhejiang University, Hangzhou, China in 2021.

Please feel free to drop me an email if you are interested in collaborating with me.

News

  • [2025.01] One paper accepted to ICLR 2025 as a Spotlight (top 5.1%).

  • [2025.01] I am currently an algorithm intern at Meituan LLM group.

  • [2024.12] I received support from the Young Scientists (Ph.D) Fund of the National Natural Science Foundation of China (¥300,000).

  • [2024.09] I won the 2024 China National Scholarship (top 0.2% in the nation).

  • [2024.09] Three papers accepted to NeurIPS 2024.

  • [2024.05] One paper accepted to ICML 2024. One paper accepted to ACL 2024.

  • [2023.11] I won the 2023 BICMR Mathematical Award for Graduate Students (top 1%).

  • [2023.09] One paper accepted to NeurIPS 2023 as a Spotlight (top 3.5%).

  • [2022.11] I have passed the Ph.D. qualifying exam.

  • [2022.10] I won the 2022 PKU Academic Innovation Award (top 1%).

  • [2022.09] Two papers accepted to NeurIPS 2022.

Research Interests

I am broadly interested in theory, algorithm and application of machine learning. I am also interested in non-convex and convex optimization.

Recently, I am dedicated to use theory to design algorithms elegantly.

My recent research topics are

  • Deep Learning Theory: optimization, generalization, implicit bias, and expressivity. [1][2][3][4][5][6][8][9][10][11][12][13]

  • Transformer and Large Language Model: theory and algorithm. [8][10][12][13]

  • Non-convex and Convex Optimization: theory and algorithm. [2][4][6][10][11][12][13]

  • CV and NLP: algorithm and application. [7][10][13]

Specifically, my research on deep learning theory and algorithm can be summarized as:

outline 

Recent Publications and Preprints

* indicates equal contribution.

Selected Awards and Honours

  • Young Scientists (Ph.D) Fund of the National Natural Science Foundation of China (¥300,000), 2024.

  • China National Scholarship (top 0.2% in the nation), The Ministry of Education, 2024.

  • Principal Scholarship, Peking University, 2024.

  • BICMR Mathematical Award for Graduate Students (top 1%), Peking University, 2023.

  • PKU Academic Innovation Award (top 1%), Peking University, 2022.

  • Outstanding Graduate of Zhejiang Province (top 5%), Zhejiang Province, 2021.

  • First Class Scholarship of ZJU (top 3%), Zhejiang University, 2019; 2020.

  • China National Scholarship (top 0.2% in the nation), The Ministry of Education, 2019.