PhD Candidate

Educational Experience:

• Master Degree in Mathematics, Courant Institue of Mathematical Sciences, New York University
• Bachelor Degree in Data Science with a concentration in Internet Finance, School of EECS, Peking University

Research Interests:

• 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

Publications:

1. Strategic Inference in Stackelberg Games: Optimal Control for Revealing Adversary Intent, joint work with D. Ralston, X. Yang, R. Hu
   In preparation
2. Finite-Agent Stochastic Differential Games on Large Graphs: II. Graph-Based Architectures, joint work with R. Hu, J. Long
   In preparation
3. Adversarial Decision-Making in Partially Observable Multi-Agent Systems: A Sequential Hypothesis Testing Approach, joint work with D. Ralston, X. Yang, R. Hu
   Submitted to IEEE TCNS
4. Integrating Sequential Hypothesis Testing into Adversarial Games: A Sun Zi-Inspired Framework, joint work with D. Ralston, X. Yang, R. Hu
   Accepted by IEEE CDC 2025
5. 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]
6. 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]
7. 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   Bachelor Thesis, not to be published

Teaching Experience:

• TA for UCSB PSTAT 213C: Graduate Level Stochastic Process (Spring 2025)
• TA for UCSB PSTAT 213B: Graduate Level Stochastic Process (Winter 2025)
• TA for UCSB PSTAT 213A: Graduate Level Stochastic Process (Fall 2024)
• TA for UCSB PSTAT 213C: Graduate Level Stochastic Process (Spring 2024)
• TA for UCSB PSTAT 213B: Graduate Level Stochastic Process (Winter 2024)
• TA for UCSB PSTAT 213A: Graduate Level Stochastic Process (Fall 2023)
• TA for UCSB PSTAT 160A: Stochastic Process (Summer 2023)
• TA for UCSB PSTAT 120A: Probability and Statistics (Spring 2023)
• TA for UCSB PSTAT 8: Transition to Data Science, Probability and Statistics (Winter 2023)
• TA for UCSB PSTAT 120B: Probability and Statistics (Winter 2023)
• TA for UCSB PSTAT 170: Introduction to Mathematical Finance (Fall 2022)
• TA for NYU MATH-UA 009: Algebra and Calculus (Spring 2022)

Other Resources:

• 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