Xiong Wang

Xiong Wang is a J.J. Sylvester Assistant Professor in the Department of Mathematics at Johns Hopkins University (non-tenure track). His research focuses on probability theory, stochastic analysis, and their applications to machine learning and complex systems. He holds a Ph.D. from the University of Alberta (2022), where he received the Faculty of Science Dissertation Award.

Education:

• Ph.D. in Mathematics, University of Alberta (2022)
• Advisor: Professor Yaozhong Hu

Research Interests:

• Probability Theory & Stochastic Processes
• Machine Learning Algorithms
• Partial Differential Equations (PDEs)
• Interacting Particle Systems
• Inverse Problems in Stochastic Dynamics
• Mathematical Foundations of Data Science

Teaching:

• Instructor for advanced courses at Johns Hopkins, including Stochastic Differential Equations, Partial Differential Equations, and Real Analysis
• Prior teaching roles at University of Alberta (Calculus, Linear Algebra)

Recent Activities:

• Speaker at over 30 international conferences/seminars since 2021
• Active in SIAM, CMS, and ICERM events
• Collaborations with institutions globally (e.g., Peking University, Brown University)