Jiacheng Zhang

I am an Assistant Professor at Department of Statistics and Data Science, The Chinese University of Hong Kong. Previously, I was a postdoctoral researcher in Industrial Engineering & Operations Research Department at Univeristy of California, Berkeley advised by Professor Xin Guo. I obtained my Ph. D. in the Department of Operations Research and Financial Engineering at Princeton University supervised by Professor Daniel Lacker and Professor Mykhaylo Shkolnikov in 2021. Prior to these, I received my bachelor's degree in Math from Tsinghua University in 2016. I can be contacted at jiachengzhang [at] cuhk [dot] edu [dot] hk Here is my CV. My research focus lies in the theory of probability and stochastic optimization. I have worked on stochastic partial differential equations, especially Mckean-Vlasov type equation, partial differential equations, mathematical finance like stochastic portfolio theory and stochastic volatility modeling in the past few years.

Papers

• Dynamics of observables in rank-based models and performance of functionally generated portfolios with Sergio A. Almada Monter and Mykhaylo Shkolnikov
  Annals of Applied Probability (2019)

• Inverting the Markovian projection, with an application to local stochastic volatility models with Daniel Lacker and Mykhaylo Shkolnikov
  Annals of Probability (2020)

• Superposition and mimicking theorems for conditional McKean-Vlasov equations with Daniel Lacker and Mykhaylo Shkolnikov
  Journal of the European Mathematical Society (2022)

• Stationary solutions and local equations for interacting diffusions on regular trees with Daniel Lacker
  Electronic Journal of Probability (2023)
  

• Agency problem and mean field system of agents with moral hazard, synergistic effects and accidents with Thibaut Mastrolia.
  Journal of Optimization Theory and Applications (2025)

• Optimization frameworks and sensitivity analysis of Stackelberg mean-field game with Xin Guo and Anran Hu
  Submitted.
  

• On time-consistent equilibrium stopping under aggregation of diverse discount rates with Shuoqing Deng and Xiang Yu
  Mathematics of Operations Research (2025)

• Deep Learning for Population-Dependent Controls in Mean Field Control Problems with Gökçe Dayanıklı and Mathieu Laurière
  Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. (2023)

• Ito's formula for flows of conditional measures on semimartingales with Xin Guo
  Electronic Journal of Probability. (2025)

• Major-Minor Mean Field Game of Stopping: An Entropy Regularization Approach with Xiang Yu, Keyu Zhang, Zhou Zhou
  SIAM Journal on Control and Optimization. (2026)

• Dimension-free error estimate for diffusion model and optimal scheduling with Valentin de Bortoli, Romuald Elie, Anna Kazeykina, Zhenjie Ren
  Transactions on Machine Learning Research (2026)

• Continuous-time mean field games: a primal-dual characterization with Xin Guo, Anran Hu and Yufei Zhang
  Submitted.
  

• Deep Signature Approach for McKean-Vlasov FBSDEs in a Random Environment with Ruimeng Hu, Botao jin and Mathieu Laurière
  Submitted.
  

Teaching

• Princeton University (TA)
  a. ORF 309 Probability and Stochastic Systems
  b. ORF 527 Stochastic Calculus
  c. ORF 526 Probability Theory
  

• University of California, Berkeley
  IND ENG 263B Applied Stochastic Process II as an co-instructor together with Professor Xin Guo.
  

• The Chinese University of Hong Kong
  a. STAT 2001 Basic Concepts in Statistics and Probability I
  b. STAT 3007 Introduction to Stochastic Processes
  c. RMSC 5102 Simulation Techniques in Risk Management and Finance
  

Award

• School of Engineering and Applied Science Award for Excellence (2021)
  This award is given to SEAS advanced graduate students who have performed at the highest level as scholars and researchers
  

• Member of Tsinghua Xuetang Training Program for excellence in academy (2012-2016)
  

• National Scholarship (2012)