Jay Bardhan, PhD

Jay Bardhan is the leader for the Computing, Analytics, and Modeling science area. Bardhan joined EMSL in May 2020, after nearly three years at GlaxoSmithKline (GSK), where he worked in a number of roles at the intersection of computing, data, and business innovation. Prior to GSK, Bardhan had spent over 15 years researching mathematical and computational models for biomolecule solvation—or the interactions between biomolecules and the surrounding solvent. His interest in solvation stems from both the intersections of his research interests (computing, biology, and physics) and the breadth of applications—environment, energy, and human health. Bardhan was originally an electrical engineer who expected to design circuits in Silicon Valley, but discovered his passion for molecular solvation and U.S. Department of Energy (DOE) mission space during his PhD, and his postdoctoral fellowship at Argonne National Laboratory.

Research Interests


Modeling biomolecule-solvent interactions
Numerical algorithms and optimization
Boundary-integral equations and partial-differential equations
Multiscale modeling


Education


PhD in Electrical Engineering, Massachusetts Institute of Technology (2006)
MS in Electrical Engineering, Massachusetts Institute of Technology (2001)
BS in Electrical Engineering, Massachusetts Institute of Technology (2000)
Wilkinson Fellowship in Scientific Computing, Argonne National Laboratory (2006 – 2008)


Awards and Recognition


Computational Science Graduate Fellowship, DOE (2002 – 2006)
Frederick A. Howes Scholar (2007)


Affiliations and Professional Service


Subcommittee Member, “Exascale Transition” for Advanced Scientific Computing Advisory Committee (2019 – 2020)
Member, Technical Program Committee (Applications Area), 2020 Supercomputing Conference
Vice-Chair, Technical Program Committee (State of the Practice Area), Supercomputing Conference (2017)
Member, Technical Program Committee (State of the Practice Area), Supercomputing Conference, (2014, 2015)
Screening and Selection Committee, Computational Science Graduate Fellowship, DOE (2008 – 2020)