Suraj Ugrani

PhD (Expected-Dec,2023) candidate in ChE at Purdue University with a diverse skillset that includes computational chemistry techniques like molecular docking, MD simulation, and homology modeling. Proficient in application of machine learning to drug discovery and programming in Python and MATLAB. Holds master's from the Indian Institute of Technology Bombay and additional professional research experience. My PhD research is focused on investigating a novel molecular descriptor and its potential application in the structure-based discovery of inhibitors of the human protease TMPRSS2, a crucial target for COVID-19 therapeutics. I am passionate about computer-aided drug discovery and excited to apply my research experience in an industrial context, particularly in drug discovery and related fields. I enjoy independently generating and executing innovative ideas, while also collaborating on interdisciplinary research. My past experience has given me an appreciation for the roles played by computational and experimental research, and how the two relate to one another.