Teaching/Students

Teaching

In the academic year Fall 2025 – Spring 2026, I teach the following courses:

• M501 – Introduction to Analysis I

• M502 – Introduction to Analysis II

• M591 – Computational Partial Differential Equations and Data

• M591 – Data-driven Deep Learning and Partial Differential Equations

The two M591 topics courses focus on partial differential equations, applied analysis, and numerical methods for PDEs, with an emphasis on connecting rigorous mathematical theory with computation and applications.

Across both undergraduate and graduate courses, my goal is to help students develop a solid analytical foundation while gaining experience with modern computational tools and learning how theoretical insight informs effective numerical modeling.

Students and Mentoring 

I have supervised and co-supervised graduate students working on topics in singular perturbation problems, boundary layer analysis, numerical methods for stiff PDEs, and hybrid analytical–computational approaches.

I welcome motivated undergraduate and graduate students, as well as postdoctoral researchers, interested in applied analysis, numerical methods, and multi-scale problems in partial differential equations, particularly those who wish to combine rigorous mathematical analysis with computation.