Our primary research interest lies in the broad area of catalysis which include reactivity study of metalloenzyme and transition metal complexes, organo-catalysts, and models of metal-organic-frameworks/covalent-organic-frameworks in order to computationally design novel catalytic systems for sustainable energy and resources. We mainly use combined density functional and wave-function based methods like the multireference and local pair natural orbital coupled cluster techniques and semi-empirical tight binding approaches to deliver a reliable picture of the catalyst active site binding, aggregation, and reaction mechanism. We also aim to use machine learning principles to design novel catalyst and new reaction pathways.
We work on problems related to physical- organic/inorganic/materials chemistry choosing appropriate computational models


