Welcome to Qinxin’s homepage!

I am Qinxin Yan, a fifth-year PhD student in the Program in Applied and Computational Mathematics (PACM) at Princeton University. I am fortunate to be advised by Prof. H. Mete Soner in the Department of Operations Research and Financial Engineering (ORFE).

My research develops asymptotic mathematical frameworks for large stochastic and strategic systems, combining control theory, game theory, and learning to analyze and design decision mechanisms in multi-agent and networked environments. I blend stochastic analysis, mean-field limits, and graph-theoretic modeling with machine-learning–based algorithms to connect rigorous theory with applications in real-world problems, such as finance and machine learning.

Previously, I was a visiting scholar with the Insurance Mathematics and Stochastic Finance Group (Group 3) in the Department of Mathematics at ETH Zurich. There, I worked with Prof. Josef Teichmann on numerical methods for mean field games, and with Prof. Beatrice Acciaio on the mean field formulation of large neural networks.

My current projects include:

• Viscosity solutions of Hamilton–Jacobi equations arising in mean field control
• Numerical methods for mean field optimal control problems and mean field games
• Large interacting particle systems with singular interactions on sparse graphs
• Applications of mean field theory and Wasserstein gradient flows in large-scale neural networks

Feel free to explore my reseach to learn more.

I am on the job market for fall 2025.