Ambarish Kulkarni

Multi-scale molecular modeling, data science for materials discovery, 
catalysis, separations

Kulkarni's research uses multi-scale molecular modeling methods to 
design and discover novel materials for applications in catalysis, 
separations and sensing. Specifically, we combine wave function theory, 
density functional theory and classical force field simulations with 
data science techniques to study complex phenomena such as aqueous-phase 
reactions, material syntheses and deactivation, hybrid catalysts and 
disordered materials. By generating fundamental, molecular level 
insight, in collaboration with experimental groups, our work finds 
applications in diverse areas such as methane upgradation, fuel cells 
and next-generation sensors.