Biography

I am a second-year Ph.D. student in Operations Research at Stanford University, honored to be advised by Prof. Aviad Rubinstein and Prof. Amin Saberi. Prior to joining Stanford, I received my bachelor’s degree at Turing Class, Peking University, where I was fortunate to be advised by Prof. Shaofeng Jiang. My research interests broadly lie in theoretical computer science and its intersection with economics and operations research.

My Chinese name is 杨明炜. I am crazy about rock climbing and I was the captain of the rock climbing team at the Mountaineering Association of Peking University.

Interests
  • Theoretical Computer Science
  • Algorithm Design and Analysis
  • Algorithmic Game Theory
Education

  • BSc (Summa Cum Laude) in Computer Science and Technology, 2019-2023

    Peking University

Publications

Süleyman Kerimov, Mingwei Yang, Sophie H. Yu (2025). Achieving Constant Regret for Dynamic Matching via State-Independent Policies. Working Paper.

Mingwei Yang, Sophie H. Yu (2025). Online Metric Matching: Beyond the Worst Case. Minor Revision at Oper. Res. (Supersedes WINE'24 paper).

Bo Li, Biaoshuai Tao, Fangxiao Wang, Xiaowei Wu, Mingwei Yang, Shengwei Zhou (2025). When is Truthfully Allocating Chores no Harder than Goods?. SAGT 2025.

Xiaohui Bei, Biaoshuai Tao, Jiajun Wu, Mingwei Yang (2025). The Incentive Guarantees Behind Nash Welfare in Divisible Resources Allocation. Artif. Intell. (Supersedes WINE'23 paper).

Zhaohua Chen, Rui Ai, Mingwei Yang, Yuqi Pan, Chang Wang, Xiaotie Deng (by contribution) (2024). Contextual Decision-Making with Knapsacks beyond Worst Cases. NeurIPS.

Amin Saberi, Mingwei Yang, Sophie H. Yu (2024). Stochastic Online Metric Matching: Adversarial is no Harder than Stochastic. WINE.

Biaoshuai Tao, Mingwei Yang (2024). Fair and Almost Truthful Mechanisms for Additive Valuations and Beyond. WINE.

Zhaohua Chen, Mingwei Yang, Chang Wang, Jicheng Li, Zheng Cai, Yukun Ren, Zhihua Zhu, Xiaotie Deng (by contribution) (2024). Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural Properties. WWW (oral).

Xiaohui Bei, Biaoshuai Tao, Jiajun Wu, Mingwei Yang (2023). The Incentive Guarantees Behind Nash Welfare in Divisible Resources Allocation. WINE.

Mingwei Yang (2023). Fairly Allocating (Contiguous) Dynamic Indivisible Items with Few Adjustments. AAMAS (Extended Abstract).

Artur Czumaj, Shaofeng H.-C. Jiang, Robert Krauthgamer, Pavel Veselý, Mingwei Yang (2022). Streaming Facility Location in High Dimension via Geometric Hashing. FOCS.

Teaching

Teaching Assistant, Design and Analysis of Algorithms,Stanford, 2025 Summer

Teaching Assistant, Incentives in Computer Science, Stanford, 2025 Spring

Teaching Assistant, Algorithm Design and Analysis, PKU, 2023 Spring

    Services

    Conference reviewer: AAMAS'24, NeurIPS'24, ICML'25, NeurIPS'25

      Contact