I work in the areas of computer-aided drug design (CADD), machine learning, and large scale virtual screening, with a focus on accelerating early-stage drug discovery. My research involves the development of machine learning–driven screening pipelines for efficient exploration of large chemical spaces. I have contributed in development of SEARCH-ML, a high-performance virtual screening platform designed for rapid triaging of millions of compounds from major chemical databases. In addition, I am actively involved in the development and validation of Sanjeevini 3.0, a comprehensive CADD web server integrating screening, docking, scoring, and toxicity prediction modules. My expertise includes molecular docking, molecular dynamics simulations, QSAR modelling, RNA-Seq analysis, and HPC based workflow development. My research aims to combine physics-based modeling with scalable machine learning approaches to build robust and accessible computational tools for the scientific community.