Richard Hennig
Professor, Alumni Professor of Materials Science & Engineering
Affiliations Computational Modeling and Simulation, Faculty, Machine Learning / Artificial Intelligence, Materials Science and Engineering
Materials Science & Engineering
Biography
Ph.D., 2000, Washington University in St. Louis
Research interests: Machine Learning and AI, Computational Modeling and Simulation, Energy Materials, Electronic Materials, Engineering Education, Nanomaterials; AI-driven and ab initio materials science; deep learning and generative models for materials prediction and inverse design; interpretable machine-learning force fields; quantum and superconducting materials; molecular magnetic qubits and spin coherence; electronic-structure and phonon-based modeling of electron–phonon coupling; electrochemical and solid–liquid interfaces; and open computational frameworks linking predictive AI, first-principles simulation, and experiment.
Lab Website: Hennig Materials Theory Lab