Fei Cao

Fei Cao is a Visiting Assistant Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. His research focuses on the interplay between interacting particle systems and partial differential equations, exploring how microscopic agent dynamics lead to macroscopic phenomena. He also investigates theoretical foundations of machine learning algorithms, particularly stochastic gradient descent.

Education:

• Ph.D. in Applied Mathematics, Arizona State University (2017–2022)
• Bachelor's degree in Applied Mathematics, Southwestern University of Finance and Economics, China (2013–2017)

Research Interests:

• Interacting particle systems and their PDE limits
• Mathematical analysis of wealth distribution models
• Opinion dynamics and collective behavior
• Theoretical computer science and machine learning mechanisms

His work bridges stochastic agent-based models with deterministic PDE frameworks, with recent focus on econophysics and gradient-based learning algorithms.

Publications Trends: Recent work emphasizes multi-phase economic models, mean-field analysis of opinion dynamics, and PDE perspectives on generative AI. His research combines analytical rigor with numerical methods to study complex systems.

No scientific awards explicitly listed. Advising no formal students listed. Active in departmental research activities.

Labs/Teams: Affiliated with the Department of Mathematics and Statistics at UMass Amherst, collaborating on interdisciplinary projects in applied mathematics and theoretical computer science.