Haosheng Zhou

Instructor Department of Operations Research and Financial Engineering Princeton University 117 Sherrerd Hall, 98 Charlton Street, Princeton, NJ 08544, USA Email: hz9769@princeton.edu You are welcome to check my CV. About me I am an instructor in the Department of Operations Research and Financial Engineering at Princeton University. I received my Ph.D. in Statistics and Applied Probability from the University of California, Santa Barbara, where I was advised by Professor Ruimeng Hu. My research focuses on stochastic control and games, multi-agent systems, and learning methods for decision-making.

• Multi-agent Games on Mathematical Structures (Graphs & Graphons)
• Multi-agent Games with Adversarial Interactions (Deception & Counter-Deception)
• Deep & Reinforcement Learning (Architectures & Algorithms) for Solving Games
• Optimal Transport and its Applications in Generative Modeling
• Signatures and its Applications in Machine Learning
• Developments and analysis of mathematical models for finance, biology, and social science

• Ph.D. in Statistics and Applied Probability, emphasis in Financial Mathematics, Department of Statistics and Applied Probability, UC Santa Barbara
• M.S. in Mathematics, Courant Institute of Mathematical Sciences, New York University
• B.S. in Data Science and Big Data Technology, concentration in Internet Finance, School of Electronics Engineering and Computer Science, Peking University

1. Optimal Design of Stealthy Attacks in Partially Observed Linear Systems: A Likelihood-Based Approach, joint work with R. Hu
   Submitted
2. Deception in Linear-Quadratic Control, joint work with Y. Kim, A. Benvenuti, R. Hu, M. Hale
   Submitted
3. Strategic Inference in Stackelberg Games: Optimal Control for Revealing Adversary Intent, joint work with D. Ralston, X. Yang, R. Hu
   Submitted
4. Learning Mean-Field Games through Mean-Field Actor-Critic Flow, joint work with M. Zhou, R. Hu
   Submitted
5. Finite-Agent Stochastic Differential Games on Large Graphs: II. Graph-Based Architectures, joint work with R. Hu, J. Long
   Communications in Nonlinear Science and Numerical Simulation , DOI: 10.1016/j.cnsns.2026.110600 [arXiv] [Journal]
6. Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach, joint work with D. Ralston, X. Yang, R. Hu
   IEEE Transactions on Control of Network Systems (TCNS), DOI: 10.1109/TCNS.2026.3690569 [arXiv] [Journal]
7. Integrating Sequential Hypothesis Testing into Adversarial Games: A Sun Zi-Inspired Framework, joint work with D. Ralston, X. Yang, R. Hu
   In Proceedings of IEEE Conference on Decision and Control (CDC) 2025, DOI: 10.1109/CDC57313.2025.11312291 [arXiv] [Conference]
8. Finite-Agent Stochastic Differential Games on Large Graphs: I. The Linear-Quadratic Case, joint work with R. Hu, J. Long
   Applied Mathematics & Optimization, DOI: 10.1007/s00245-025-10309-8 [arXiv] [Journal]
9. Detecting Boolean Asymmetric Relationships with a Loop Counting Technique and its Implications for Analyzing Heterogeneity within Gene Expression Datasets, H. Zhou, W. Lin,
   S.R. Labra, S.A. Lipton, J.A. Elman, N.J. Schork, A.V. Rangan
   IEEE/ACM Transactions on Computational Biology and Bioinformatics, DOI: 10.1109/TCBB.2024.3487434 [bioRxiv] [Journal]
10. Approximation Algorithms and PTAS of the Minimum Dominating Set and the 3-Path Vertex Cover Problem on Unit Disk Graphs, H. Zhou, J. Tu, Y. Kong
    Bachelor Thesis, not to be published

• Princeton ORF 418: Optimal Learning (Fall 2026)
• Past TA Experience and Materials

• RSS Feed for arXiv Preprints
• Notes and Codes
• A website for particle system simulation, constructed with L.T. Rolla, X. Ma, and Y. Dai
• Some maths notes in Chinese posted on Zhihu