Weitang Li Group - Teaching
2026
Fall, MAT3300: Mathematical Modeling
- Topics: Modeling process, empirical model fitting, Monte Carlo simulation, optimization, graph theory, ODEs, machine learning and deep learning, multi-criteria decision analysis, metaheuristics, and game theory, with MCM/ICM case studies.
Fall, AIS5007: Principles of Quantum Mechanics and Quantum Computation
- Topics: Quantum mechanics foundations, quantum circuits and algorithms, Hamiltonian simulation, variational quantum algorithms, quantum machine learning, and noise and error mitigation, with applications in quantum chemistry.
Summer, EUSC x AISE Summer Camp: AI for Chemistry and Materials Science
- Co-Instructor: Zhihai Ke
- Topics: Recent advances in AI for chemistry and materials science
Spring, CHM 6503 / MSE 6207: Advanced Computational Chemistry
- Topics: Python foundations, cluster computing, quantum chemistry, machine learning for molecular property prediction, and advanced AI methods including GNNs.
2025
Fall, MAT3300: Mathematical Modeling
- Co-Instructor: Chaoyu Quan
- Topics: Modelling techniques for problems in physics, biology and economics. Elements of ODEs, optimization and machine learning.
Summer, AISE Summer Camp: AI for Physics and Chemistry
Spring, CSC1006: Artificial Intelligence for Science and Engineering
- Co-Instructors: Kai Zhou, Fangxun Zhong
- Topics: Elements of sklearn and applications in science and engineering
2024
Fall, MAT3300: Mathematical Modeling
- Co-Instructor: Paolo Piersanti
- Topics: Modelling techniques for problems in physics, biology and economics. Elements of ODEs, optimization and machine learning.
