About

I am a second-year Computer Science PhD student at Stanford Theory Group, where I am advised by Ashish Goel and co-advised by Aviad Rubinstein. My research lies at the interface of computer science and economics, with broad interests in algorithmic game theory, mechanism design, social choice, optimization, and complexity theory. I study how strategic agents interact through algorithms and platforms, especially when communication, information, or computational resources are limited, with the goal of designing mechanisms with rigorous guarantees and understanding the fundamental limitations. My work spans market design, collective decision-making, and blockchain systems. More recently, I am interested in how strategic interactions shape the behavior and performance of LLM-based systems, particularly interation between user and agents (delegation), between agents (multi-agent systems) and agents and the platform.

I completed my undergraduate degree in Computer Science and Cognitive Science at University of Virginia, where I had the pleasure of working with Haifeng Xu (now at the Department of Computer Science and Data Science Institute at UChicago). After graduation, I spent a year working with Pinyan Lu as a visiting student at Shanghai University of Finance and Economics. In May 2024, I graduated with an M.S.E. in Computer Science from Princeton University, where I was very fortunate to be advised by Matt Weinberg. Check here for my CV.


Manuscripts

    Discrete-Core Nonemptiness for Approval Elections with at Most Eight Voters [pdf]

    Chenghan Zhou

    Strategic Delegation for Welfare and Representation under Limited Communication

    (α-β) Ashish Goel, Chenghan Zhou

    Hardness of Approximate Hylland-Zeckhauser Equilibria [arxiv]

    (α-β) Mark Braverman, Jingyi Liu, Eric Xue, Chenghan Zhou

    Stronger Core Results with Multidimensional Prices [arxiv]

    (α-β) Mark Braverman, Jingyi Liu, Eric Xue, Chenghan Zhou


Publications

    Short Paper: Knapsack Voting for Concurrent Block Proposals [pdf]

    Geoffrey Ramseyer, Chenghan Zhou, Ashish Goel
    DeFi 2026: 5th Workshop on Decentralized Finance (DeFi), in association with Financial Cryptography 2026 (FC'26).

    Analyzing the Economic Impact of Decentralization on Users [arxiv]

    (α-β) Amit Levy, S. Matthew Weinberg, Chenghan Zhou
    ITCS 2026: The 17th Innovations in Theoretical Computer Science.

    Profitable Manipulations of Cryptographic Self-Selection are Statistically Detectable [arxiv]

    (α-β) Linda Cai, Jingyi Liu, S. Matthew Weinberg, Chenghan Zhou
    AFT 2024: The 6th International Conference on Advances in Financial Technologies.

    Better Approximation for Interdependent SOS Valuations [arxiv]

    (α-β) Pinyan Lu, Enze Sun, Chenghan Zhou
    WINE 2022: The 18th Conference on Web and Internet Economics.

    Information Design for Multiple Independent and Self-Interested Defenders: Work Less, Pay Off More [pdf]

    Chenghan Zhou, Andrew Spivey, Haifeng Xu, Thanh Hong Nguyen
    UAI 2022: The 38th Conference on Uncertainty in Artificial Intelligence (also accepted to Games Journal).

    Algorithmic Information Design in Singleton Congestion Games [arxiv]

    Chenghan Zhou, Thanh H. Nguyen, Haifeng Xu
    EC 2022: Proc. 23th ACM Conference on Economics and Computation.


Teaching


Service

Honor


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