Kevin Greenman completed his Ph.D. in chemical engineering and computation at the Massachusetts Institute of Technology (MIT), where he was a National Science Foundation graduate research fellow. His research focuses on using artificial intelligence and physics-based simulations to discover new molecules and materials. Currently, he is working on designing molecules with specific optical properties for use in display technologies and medical imaging. During his Ph.D., Kevin gained practical experience through internships in drug discovery at Eli Lilly and in protein engineering at Microsoft Research. He holds a Bachelor of Science in Engineering (B.S.E.) degree in chemical engineering from the University of Michigan, graduating summa cum laude. His studies included a concentration in materials science and engineering and a minor in mathematics. During his undergraduate studies, Kevin spent a summer at Purdue University’s Network for Computational Nanotechnology developing a web-based tool for computational catalysis research and education. He also spent a summer studying at the Hong Kong University of Science and Technology. Kevin has experience teaching both undergraduate and graduate students at MIT. He also co-designed a new course during his undergraduate years at the University of Michigan. He has been active in the Tech Catholic Community at MIT throughout his Ph.D., helping to organize lectures through the Thomistic Institute. He is a co-founder and co-president of the Harvard-MIT chapter of the Society of Catholic Scientists.

Featured Publications:

Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back

Chemprop: A Machine Learning Package for Chemical Property Prediction