Teaching

Graduate Courses

MASC 575: Basics of Atomistic Simulation of Materials
MASC 576: Molecular Dynamics Simulations of Materials and Processes

This course introduces modern computational materials modeling from large-scale materials simulations, quantum-mechanical (QM) simulations via Density Functional Theory (DFT), machine-learning interatomic potentials (MLIPs) and foundation models, and agentic AI tools for science and engineering students. The landscape of computational materials science is rapidly changing. DFT has become a standard theoretical tool for predicting materials properties, and high-performance advanced computing provides the scale needed to apply it broadly. Remarkable progress in machine learning (ML) has produced universal interatomic potentials that approach QM accuracy at a fraction of the cost. The most advanced AI agents now help researchers explore new materials, reason through literatures and simulations, and orchestrate the workflows that connect them. In this course, students build frontier skills across a wide spectrum of computational materials science from high-performance-computing simulations, QM calculations to state-of-the-art ML and agentic AI.

MASC 515: Basics of Machine Learning for Materials
MASC 520: Mathematical Methods for Deep Learning

These courses introduce Machine Learning (ML) and Python programming essentials for data-driven science and engineering. Artificial Intelligence (AI), Deep Learning (DL), Reinforcement Learning (RL), and Large Language Models (LLMs) are rapidly transforming how we interact with technology, and the fast pace of the field can make it challenging for beginners to enter. Python has become the industry standard for ML, and basic software engineering skills and literacy are essential for moving from theoretical knowledge to real-world application. The courses are designed for students from any engineering or science background — no prior experience with ML or Python programming is required.

Undergraduate Courses

MASC 110L: Materials Science
AME 231: Mechanical Behavior of Materials
CHE 405: Applications of Probability and Statistics for Chemical Engineers