Dr. 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.