Curriculum vitae
Qinxin Yan
University of California, Berkeley · Berkeley, California
qinxinyan@berkeley.edu · qinxin-yan.github.io · github.com/Qinxin-Yan
Appointments
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PresentPostdoc, University of California, BerkeleyGroup of Prof. Xin Guo
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2023 – 2024Visiting Scholar, ETH ZürichInsurance Mathematics and Stochastic Finance, Department of Mathematics · with Prof. Josef Teichmann and Prof. Beatrice Acciaio
Education
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2021 – 2026Ph.D., Program in Applied and Computational MathematicsPrinceton University · Advisor: Prof. H. Mete Soner
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2017 – 2021B.S., Computational MathematicsUniversity of Science and Technology of China
Research interests
Mean-field control and games; McKean–Vlasov control and viscosity solutions on Wasserstein space; Wasserstein gradient flows and optimal transport; interacting particle systems on graphs and systemic risk; machine-learning methods for stochastic control and multi-agent games.
Publications
Journal articles
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Learning Algorithm for Mean Field Optimal Control
SIAM Journal on Numerical Analysis, 2026. To appear.
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Iterative Schemes for Markov Perfect Equilibria
Mathematical Finance, 2026. To appear.
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Viscosity Solutions of the Eikonal Equation on the Wasserstein Space
Applied Mathematics and Optimization, 2024.
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Viscosity Solutions for McKean–Vlasov Control on a Torus
SIAM Journal on Control and Optimization, 60(6):3797–3824, 2022.
Preprints
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Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data
arXiv:2606.26498, 2026.
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Policy Gradient for Continuous-Time Mean-Field Control
arXiv:2605.20718, 2026.
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Implicit Regularization of Large Neural Networks via Mean-Field Formulation
arXiv:2603.20892, 2026.
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Particle Systems with Local Interactions via Hitting Times and Cascades on Graphs
arXiv:2505.18448, 2025.
Talks
- Oct 2025Singular Interacting Particle System and Default Cascade on Sparse GraphPACM Graduate Student Seminar, Princeton University
- Jul 2025Learning Algorithm for McKean–Vlasov ControlSIAM Conference on Financial Mathematics and Engineering
- Jun 2024Kuramoto Optimal Control Problem and Its Numerical MethodsETH–Hong Kong–Imperial Mathematical Finance Workshop
- Apr 2024Machine Learning-Based Numerical Methods for Mean Field Control ProblemsOxford–ETH Workshop in Financial Mathematics
- Sep 2023Comparison Principle for Viscosity SolutionsWPI Workshop: Stochastics, Statistics, Machine Learning and Their Applications to Sustainable Finance and Energy Markets
- Apr 2023Viscosity Solutions for McKean–Vlasov Control on a TorusORFE Graduate Student Seminar, Princeton University
- Mar 2023Viscosity Solutions for McKean–Vlasov Control on a TorusPACM Graduate Student Seminar, Princeton University
- Sep 2022Correlation Between Mean Field Games and McKean–Vlasov ProblemsORFE Graduate Student Seminar, Princeton University
Teaching
- Fall 2025Optimal LearningTeaching Assistant, Princeton University · 75 students
- Spring 2025Advanced Linear AlgebraTeaching Assistant, Princeton University · 34 students
- Fall 2024Numerical Analysis and Scientific ComputingTeaching Assistant, Princeton University · 35 students
- Spring 2024Introduction to Financial MathematicsCoordinator, ETH Zürich · 120 students
- Spring 2023Numerical MethodsTeaching Assistant, Princeton University · 10 students
- Fall 2022Linear AlgebraTeaching Assistant, Princeton University · 126 students
Service & mentoring
- Organizer, Directed Reading Program (DRP), Department of Mathematics, Princeton University.
Software
- Mean-Field-Control — Python implementation of the neural-network algorithm for mean-field control. github.com/Qinxin-Yan/Mean-Field-Control
- Picard-Iteration-For-Finite-Player-Game — iterative schemes for Markov perfect equilibria in finite-player games. github.com/Qinxin-Yan/Picard-Iteration-For-Finite-Player-Game