Teaching

This course introduces students to the principles and applications of machine learning and quantum computing in chemistry research. Topics include neural networks, quantum algorithms, and computational methods for molecular systems.

An introduction to quantum mechanics with applications to atomic and molecular spectroscopy and computational chemistry. Topics include the Schrödinger equation, eigenfunctions, operator algebra, and applications to chemical systems.

This advanced course builds on the principles of quantum mechanics and explores their applications in molecular spectroscopy and quantum chemistry. Topics include perturbation theory, density functional theory, and computational methods for excited states.

Chemistry 114 introduces the fundamentals of chemistry and chemical reactivity with emphasis on scientific problem-solving skills through lectures and discussion sections devoted to quantitative reasoning

With a focus on computational modeling and physical principles