Tom Miller was born in San Diego, California and grew up in College Station, Texas. After completing his undergraduate degree at Texas A&M University, he attended graduate school in the UK on a British Marshall Scholarship and received his Ph.D. from Oxford University in 2005, working with David Clary and David Manolopoulos. Tom then returned to the US for a postdoctoral fellowship at UC Berkeley to work with David Chandler and Bill Miller. He joined the faculty of the California Institute of Technology in 2008 and was promoted to full professor in 2013. While at Caltech, Tom has received awards that include the Sloan Research Fellowship, NSF CAREER Award, Associated Students of Caltech Teaching Award, Dreyfus Teacher-Scholar Award, and the ACS Early-Career Award in Theoretical Chemistry.
Jorge Emiliano Deustua Stahr
Emiliano obtained his PhD in Chemistry from Michigan State University, where he developed new methodologies in quantum chemistry by merging deterministic coupled-cluster calculations with stochastic wave function sampling. Currently, he works on using machine learning to develop tractable approaches that aim for a better understanding of batteries and other condensed-phase systems.
Jorge obtained a BS in chemical engineering from the University of Puerto Rico at Mayaguez. His PhD work focuses on the development and analysis of high-dimensional sampling methods for the simulation of (non-)equilibrium molecular systems.
Daniel earned his BS in chemical engineering from Brown University before spending two years applying enhanced sampling methods to protein-protein complexes at D. E. Shaw Research. He received the Department of Energy Computational Sciences Graduate Fellowship to pursue his PhD work on understanding dendrite formation in lithium metal batteries and the development of next generation solid polymer electrolytes.
Matthew received a MChem in chemistry from the University of Oxford, UK. He currently uses atomistic and coarse-grained molecular dynamics simulations to investigate the behavior of proteins as they are translated by the ribosome.
Xuecheng earned a B.Sc. in chemical physics from University of Science and Technology of China. His current work is focusing on developing novel theoretical methods in quantum dynamics and applying them to the non-adiabatic processes in the condensed phase.
Jeongmin received a MS in chemistry from Sogang University, South Korea for his work on heterogeneous dynamics in soft materials. His PhD work aims at understanding a polymer electrolyte/electrode interface for battery applications.
Sherry received a BS in Chemistry/Math/Biochemistry/Molecular Biology and a minor in Computer Science from University of Wisconsin-Madison. She was awarded a Caltech graduate fellowship. Her current research focuses on developing Molecular Orbital-Based Machine Learning (MOB-ML) method for electronic structure, and nucleic acid secondary structure modeling using machine learning and molecular dynamics tools.
Roman obtained his BS in Chemistry from the University of Toronto, Canada, where he studied conductance of DNA molecules. He was awarded a Caltech graduate fellowship and he is currently working on the dynamics of various chemical systems using mixed quantum-classical approaches.
Marta obtained a bachelor’s in chemistry from the Autonomous University of Barcelona. She has been awarded a “La Caixa” Foundation postgraduate fellowship and is currently working on building models to predict nucleic acid secondary structure.
James earned his BS in Chemistry and Mathematics from the University of Michigan, Ann Arbor, where he studied transition metal catalysis and proteomics. He was awarded a NSF GRFP fellowship and is currently working on applying cost-efficient embedded mean field theory to elucidate the reactivity of polyolefin catalysts.
Jiace obtained his BS in Physics from the University of Science and Technology of China and worked on electronic structure of graphene nanoribbon using quantum embedding method. He is currently developing generalized modifications of ring-polymer molecular dynamics.
Zhuoran earned his B.Sc. in Chemistry from Peking University where he worked on anisotropic dynamics in nanoconfined soft matters. He is currently working on developing molecular orbital based machine learning methods for molecular design.
Huanghao (Doris) Mai
Doris obtained her BS in Biocomputation from Stanford University, where she worked on predicting protein-ligand binding using machine learning. She currently uses molecular dynamics simulations for mechanistic studies of complex biological systems.
GS = Graduate Student, PD = Postdoctoral Scholar, UG = Undergraduate Student, VS = Visiting Scholar
Nandini Ananth (PD)
Bernardo Araujo (GS)
Universidad Nacional de Tucumán
Taylor Barnes (GS)
Franziska Bell (PD)
Vice President, Data & Analytics
Nick Boekelheide (GS)
Peter Bygrave (PD)
Lead Software Engineer
Ioan Bogdan-Magdau (PD)
Leanne Chen (PD)
University of Guelph
Connor Coley (UG)
Feizhi Ding (PD)
Lead Software Engineer
Lila Forte (GS)
University of Colorado, Boulder
Todd Gingrich (UG)
Jason Goodpaster (GS)
University of Minnesota, Twin Cities
Pengfei Huo (PD)
University of Rochester
Tamara Husch (PD)
Helmholtz-Zentrum Berlin (HZB), Berlin
Jakub Kaminski (PD)
Cloud Computing Platform Engineer
Arvind Kannan (UG)
Senior Computational Physicist
Josh Kretchmer (GS)
Joonho Lee (GS)
Sebastian Lee (GS)
AI Research Scientist
Aleph One (LF1), Berlin
Matt Mayers (UG)
Yongle Li (VS)
Artur Menzeleev (GS)
Co-founder & Chief Science Officer
Stephen Munoz (PD)
Michiel Niesen (GS)
Saleh Riahi (PD)
Varun Rishi (PD)
Romelia Salomón-Ferrer (PD)
Brett Savoie (PD)
Philip Shushkov (PD)
Eric Sundstrom (PD)
Senior Software Engineer, Data Infrastructure
Reid Van Lehn (PD)
University of Wisconsin-Madison
Connie Wang (GS)
Mike Webb (GS)
Matt Welborn (PD)
Co-founder & Principal Scientist
Lead Software Engineer
Ralph Welsch (PD)
Deutsches Elektronen-Synchrotron (DESY), Hamburg