William A. Goddard, III is the Charles and Mary Ferkel Professor of Chemistry, Materials Science, and Applied Physics and Director of the Materials and Process Simulation Center (MSC) at California Institute of Technology, where he has been on the faculty since November, 1964. He was Elected Member of National Academy of Science in 1984, the International Academy of Quantum Molecular Science in 1988, Fellow of American Physical Society in 1988, Fellow of American Association for the Advancement of Science in 1990, Fellow of the Royal Society Chemistry in 2008, and Fellow of American Academy of Arts and Sciences in 2010. His awards include ACS Computers in Chemistry (1988), Richard M. Badger Teaching Prize in Chemistry, Caltech (1995); Feynman Prize for Nanotechnology Theory (1999), Richard Chase Tolman Prize CA ACS (2000); Honoris Causa Philosophia Doctorem (Chemistry, Uppsala U., Sweden, 2004); ACS Theoretical Chemistry (2007); NASA Space Sciences (sensors 2009 and polymers 2012); Distinguished Scientific Achievement in Catalysis from the 7th World Congress on Oxidation Catalysis (2013). His current research interests include new methodology for quantum chemistry, reactive force fields, reactive dynamics, and electron dynamics with applications of atomistic simulations to chemical, biological, and materials systems, including homogenous and heterogeneous catalysis, electrocatalysis, polymers, semiconductors, superconductors, metal alloys, fuel cells, batteries, energetic materials, nanoelectronics, GPCR protein structure prediction, drug design and materials under extreme conditions. Dr. Goddard is a co-founder of Schrödinger and a chairman of the Scientific Advisor Board on Materials Sciences.
Michael K. Gilson, M.D, Ph. D.
Dr. Gilson has 25 years of experience developing methods and tools for molecular modeling in chemistry and the life sciences. He made fundamental contributions to the development of the Poisson-Boltzmann model of molecular electrostatics and to widely used programs implementing this model. More recently, he has developed the predominant states approach to calculating molecular binding affinities. He received his undergraduate degree from Harvard College in Bioengineering, Ph.D. from Columbia University in Biochemistry and Molecular Biophysics, and M.D. from Columbia University College of Physicians and Surgeons. He is concurrently Professor and Chair of Computer-Aided Drug Design, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego.
Tom Kurtzman, Ph. D.
Tom Kurtzman, PhD, is an associate professor at Lehman College, City University of New York, where his research focuses on the development of computational methods that aid in the discovery and rational design of new drugs. Professor Kurtzman’s approach applies a combination of statistical mechanical theory and computer simulations to better understand the physical principles governing the molecular recognition between proteins and small molecule drug candidates. His research contributions provide a framework to account for and quantify the role that water plays in molecular recognition.
Dr. Kurtzman’s honors and awards include the OpenEye Outstanding Junior Faculty Award from the Computational Chemistry Division of the American Chemical Society. Dr. Kurtzman earned a bachelor of arts degree in chemistry from the University of California, Santa Cruz, a doctor of philosophy degree in chemistry from Stanford University, and pursued postdoctoral research at Columbia University.
Cheol Ho Choi, Ph. D.
Professor Cheol Ho Choi’s current research interests focus on the development of quantum mechanical methodologies for electronic state properties and their application to modeling the non-adiabatic dynamics. Recently developed MRSF-TDDFT (Mixed Reference Spin-Flip Time Dependent Density Functional Theory) is an efficient yet accurate quantum mechanical platform, introducing the multi-reference features to the ground and excited electronic states. In MRSF, the electronic ground and excited states are obtained from the poles of a novel mixed reference (MR) within the linear response (LR) regime. With the help of a novel spinor-like transformation, a hypothetical single reference is constructed from the M_s=1 and -1 components of the restricted open-shell KS determinant, expanding its response space significantly.