Fan Yao

Assistant Professor at STOR@UNC

The University of North Carolina at Chapel Hill

Biography

I am an assistant professor in the Department of Statistics and Operations Research at UNC Chapel Hill. I received my PhD in Computer Science at the University of Virginia, advised by Prof. Haifeng Xu and Prof. Hongning Wang. My current research focuses on modeling human–AI interactions, with the aim of understanding their broader societal impacts and designing interventions that foster social good. I use mathematical tools including statistical learning theory, algorithmic game theory, online learning, and optimization.

I am seeking self-motivated students with strong mathemetical foundations and Python programming skills to work with me. Students from both UNC and other institutions are welcome. If you are interested in this opportunity, please contact me directly via email expressing your research interests with your CV.

Download my resumé.

Interests

Social aspects of AI
Multi-agent modeling
Algorithmic game theory
Online learning

Education

Ph.D. in Computer Science, 2025

University of Virginia
Bsc./MSc. in Computational Mathematics, 2016

Peking University

Working Papers

indicates equal contribution, authors in alphabetical order.

The Complexity of Tullock Contests

Yu He, Fan Yao, Yang Yu, Xiaoyun Qiu, Minming Li, Haifeng Xu

Last updated on Dec 9, 2024

Strategic Filtering for Content Moderation: Free Speech or Free of Distortion?

Saba Ahmadi, Avrim Blum, Haifeng Xu, Fan Yao

Last updated on Oct 31, 2024

Publications

indicates equal contribution, authors in alphabetical order.

Haruka Kiyohara, Fan Yao, Sarah Dean (2025). Policy Design for Two-sided Platforms with Participation Dynamics.
ICML, 2025.

PDF

Yaolong Yu, Fan Yao, Sinno Jialin Pan (2025). Beyond Self-Interest: How Group Strategies Reshape Content Creation in Recommendation Platforms?.
ICML, 2025.

PDF

Fan Yao, Yuwei Cheng, Ermin Wei, Haifeng Xu (2024). Single-Agent Poisoning Attacks Suffice to Ruin Multi-Agent Learning.
ICLR, 2025.

PDF Source Document

Yuwei Cheng, Fan Yao, Xuefeng Liu, Haifeng Xu (2024). Learning from Imperfect Human Feedback: a Tale from Corruption-Robust Dueling.
ICLR, 2025.

PDF Cite Source Document

Fan Yao, Yiming Liao, Jingzhou Liu, Shaoliang Nie, Qifan Wang, Haifeng Xu, Hongning Wang (2024). Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms.
Neurips, 2024.

PDF Video Source Document

Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu (2024). Human vs Generative AI in Content Creation Competition: Symbiosis or Conflict?.
ICML, 2024
Oral presented at Econometric Society Interdisciplinary Frontiers (ESIF) conference on Economics and AI+ML.

PDF Source Document

Fan Yao, Yiming Liao, Mingzhe Wu, Chuanhao Li, Yan Zhu, James Yang, Jingzhou Liu, Qifan Wang, Haifeng Xu, Hongning Wang (2024). User Welfare Optimization in Recommender Systems with Competing Content Creators.
KDD, 2024.

PDF Source Document

Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman, Yiming Liao, Yan Zhu, Qifan Wang, Hongning Wang, Haifeng Xu (2023). Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?.
Neurips, 2023.

PDF Source Document

Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu (2023). How Bad is Top- Recommendation under Competing Content Creators?.
ICML, 2023 (oral presentation, 2.4%).

PDF Video Source Document

Fan Yao, Chuanhao Li, Denis Nekepalov, Hongning Wang, Haifeng Xu (2022). Learning from a Learning User for Optimal Recommendations.
ICML, 2022
Selected as spotlight presentation at ICML, 2023, Workshop on Interactive Learning with Implicit Human Feedback.

PDF Cite Source Document

Jibang Wu, Haifeng Xu, Fan Yao (2022). Multi-Agent Learning for Iterative Dominance Elimination: Formal Barriers and New Algorithms.
COLT, 2022
Extended version under major revision at JMLR.

PDF Cite Source Document

Fan Yao, Chuanhao Li, Denis Nekepalov, Hongning Wang, Haifeng Xu (2022). Learning the Optimal Recommendation from Explorative Users.
AAAI, 2022.

PDF Cite Source Document

Fan Yao, Renqin Cai, Hongning Wang (2022). Reversible Action Design for Combinatorial Optimization with Reinforcement Learning.
AAAI-ML4OR, 2022.

PDF Cite Source Document

Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao (2021). PAC-Learning for Strategic Classification.
The Journal of Machine Learning Research (JMLR)
Shorter version at ICML, 2021 (oral presentation, 3%).

PDF Cite Poster Video Source Document

Experience

Graduate Research Assistant

University of Virginia

Aug 2019 – Present Charlottesville, US

Ph.D. candidate in CS department

Visiting Student

University of Chicago

May 2023 – Present Chicago, IL

Multi-agent and economic modeling for online content market.

Student Researcher

Meta Research

Dec 2023 – Jul 2024 Menlo Park, CA

Host: Dr. Qifan Wang
Deploy mechanism design solutions for improving user engagement on Instagram Reels.

Student Researcher

Google Research

May 2022 – Sep 2022 Mountain View, CA

Manager: Dr. Chih-wei Hsu, Dr. Craig Boutilier
Bayesian preference elicitation in interactive recommender systems using Concept Activation Vectors.

Research Intern

ByteDance (TikTok) AML Lab

May 2021 – Aug 2021 Seattle, WA (remote)

Manager: Dr. Chong Wang, Dr. Taiqing Wang
Enhance the recommendation diversity and mitigate the echo chamber effect via collaborative Thompson sampling approach and gradient-based Determinantal Point Processes.