I am an Assistant Professor at SR University with a Ph.D. in Physics and over 12 years of research experience in computational materials science. My expertise lies in Density Functional Theory (DFT), Time-Dependent DFT (TDDFT), ab initio molecular dynamics, and machine learning approaches for materials modelling and discovery.

My current research focuses on understanding the electronic and optical properties of materials, designing efficient catalysts for plasmon-assisted chemical reactions, and investigating semiconductor interfaces for optoelectronic applications. I am also exploring graph neural networks, transfer learning, and neural operators to accelerate materials simulations and enable data-driven materials discovery.

My teaching interests include Python programming, computational physics, artificial intelligence, machine learning, and their applications in scientific research. I am particularly interested in integrating computational tools, hands-on learning, and AI-assisted problem-solving into teaching while mentoring students toward interdisciplinary research and innovation.