Yash Mathur is currently working as a PhD candidate at the Centre for Interdisciplinary Research in Basic Sciences (CIRBSc), Jamia Millia Islamia (JMI), New Delhi, India ​. He is pursuing a PhD in Computational Biology, with research focused on generative deep learning for drug discovery, designing automated in-silico pipelines that integrate molecular docking, molecular dynamics simulations and cheminformatics analyses to streamline therapeutic candidate identification.

His areas of interest include computational drug discovery, structural bioinformatics, artificial intelligence, and scientific software development. As part of his doctoral research, he is working on a project titled "Employing Generative Deep Learning Models for Strategic Advancements in Drug Development," which aims to streamline therapeutic candidate identification by combining predictive modeling with high-throughput molecular screening techniques.

He holds an M.Sc. in Bioinformatics and a B.Sc. in Microbiology, and is UGC NET-qualified (AP Category) in Computer Science. His published work spans genome-wide cancer studies, structure-based drug design, and the development of user-friendly computational tools. Yash’s technical expertise includes sequence analysis, protein-ligand interaction modeling, high-throughput docking, molecular dynamics, and AI-driven molecular design. He is especially interested in building scalable, reproducible pipelines and intuitive interfaces that make complex biological analyses more accessible.