teaching

Numerical methods for the standard problems of scientific computing: root finding, interpolation, quadrature, linear systems, and ordinary differential equations.

Vector geometry, partial derivatives, multiple integrals, line and surface integrals, and the classical theorems of Green, Stokes, and Gauss.

First- and second-order ordinary differential equations, linear systems, Laplace transforms, and series solutions, with engineering applications.

Multivariable calculus — partial derivatives, multiple integrals, vector calculus, and Green/Stokes/Gauss theorems.

Core numerical methods of scientific computing: root finding, interpolation, quadrature, linear systems, and ODEs — with Python implementations.

Combinatorics, graph theory, recurrence relations, generating functions, and discrete probability — the discrete-mathematics foundation for computer science and operations research.

Linear programming, the simplex method, duality, sensitivity analysis, integer programming, and network flows.

Combinatorics, graph theory, recurrence relations, and discrete probability — discrete-mathematics foundations for CS and operations research.

A summary of teaching at SUNY Korea (2017–2023), Vietnamese-German University (2016), and Wayne State University (2012–2016, as a graduate teaching assistant).