Joseph Morrone

Joseph A. Morrone is engaged in exploring advances in deep learning and structure-based drug discovery, as well as generating and curating relevant datasets for use in these approaches. He has developed formative graph-based deep learning architectures that input three-dimensional molecular representations to enhance small molecule docking and molecular dynamics simulation. He is also interested in the application and development of molecular simulation techniques in the fields of biophysics and chemistry, and in turn utilizing such simulations as a data resource.

Before joining IBM, Morrone was a Junior Research Fellow in the Laufer Center for Physical and Quantitative Biology at Stony Brook University.  He obtained his Ph.D. from Princeton University, his B.S. from New York University, and completed his postdoctoral training at Columbia University.  Highlights of his past work include uncovering how nuclear quantum effects impact hydrogen bonds and how molecular scale hydrodynamics and slow fluctuations associated with hydrophobic interactions influence the kinetics of self-assembly.  He has also worked on applying these techniques more broadly to study bio-molecular motion and association. He has co-authored numerous publications and his research has been featured in the New Scientist and the Water in Biology blog.