Quantum AI Approaches Towards Drug Design

Abstract

One of the hardest problems in healthcare today is identification of drug candidates for targets relevant for diseases like cancer. Finding a drug candidate is analogous to finding a needle in the haystack. As a result, drug discovery takes decades and costs billions of dollars. Traditional computational approaches rely on machine learning which requires millions of training parameters and still fails to find high-quality drug candidate with likelihood to pass the clinical trial. This talk will illustrate viable pathways to harness the computational power of quantum computers and quantum AI to address drug design problems.

Bio

Dr. Swaroop Ghosh holds a Ph.D. from Purdue University. He is currently Professor of Electrical Engineering at Penn State University. He has received 20+ awards for excellence in research, advising and teaching most notably DARPA Young Faculty Award and Director’s Fellowship, ACM SIGDA Outstanding New Faculty Award, IEEE Computer Society’s TCVLSI Mid-Career Award and NAGS Geoffrey Marshall Mentoring Award. He has also received 6 Best Paper Awards. Dr. Ghosh is a Fellow of the IEEE, the National Academy of Inventors and the Asia-Pacific AI Association (AAIA). His current research interests include circuit design, hardware security and quantum computing.