Sharath B S, M.Sc., Ph.D.

I hold a Ph.D. in Biotechnology and have held postdoctoral research positions at Soongsil University (South Korea) and the University of Vienna (Austria), where I broadened my expertise in computational biology, cheminformatics, machine learning, and AI-assisted drug discovery. At Soongsil University, I specialized in High-Performance Computing (HPC) and computational chemistry, developing automated high-throughput virtual screening pipelines for large-scale compound libraries and engineering robust cheminformatics workflows to accelerate early-stage drug discovery. These experiences strengthened my ability to design scalable computational pipelines for data-intensive scientific applications. At the University of Vienna, I collaborated with Roche Pharmaceutical to develop machine learning–driven preclinical frameworks that leveraged historical in vivo datasets to improve experimental design and reduce the reliance on control groups. This work further expanded my expertise in predictive modeling, data analytics, and translational drug discovery. Currently, I am a Research Scientist at UR Advanced Therapeutics, where I develop computational workflows for peptide therapeutics, molecular modeling, molecular dynamics (MD) simulations, and multiomics data analysis. My research focuses on integrating computational chemistry, bioinformatics, and artificial intelligence (AI) to accelerate therapeutic discovery and generate biologically meaningful insights from complex datasets. My broader research interests lie at the intersection of AI, computational chemistry, cheminformatics, molecular modeling, bioinformatics, and multiomics. I enjoy building scalable scientific software, developing reproducible computational workflows, and applying advanced computational methods to solve challenging biological problems. I am particularly passionate about combining machine learning, molecular simulations, and multiomics analytics to advance next-generation drug discovery and precision medicine.