The Chen group develops and applies theoretical, simulation, and machine learning (ML) methods for elucidating mechanistic details giving rise to chemical and physical phenomena in condensed phase systems ranging from charge transport in battery electrolytes to energy relaxation pathways of fluorophore probes and the self-assembly of colloidal crystals. We are interested in tackling the challenges of accurately modeling these and other dynamical processes where electronic and nuclear quantum effects (NQEs) need to be treated to accurately model experimental observables of interest.
Michael Chen
Assistant Professor, Chemical Engineering (Joint Appointment Computer Science)
Research Description
Research Interests
- Theoretical and Computational Chemistry
- Quantum Effects in Molecular and Materials Systems
- Artificial Intelligence and Machine Learning
- Vibrational and Electronic Spectroscopies
- Electrochemistry and Charge Transport
- Colloidal Self-Assembly
Education
Ph.D., Stanford University, Chemistry, 2023
B.Sc., UC Berkeley, Chemistry, 2016
B.A., UC Berkeley, Computer Science, 2016
Appointments
2023-2026: Independent Postdoctoral Fellow, Simons Center for Computational Physical Chemistry, New York University