Ahmadi wins lightning talk at Broad Institute’s Machine Learning in Drug Discovery Symposium

Brown doctoral student Nazanin Ahmadi took top honors in the lightning talks at the Broad Institute Machine Learning in Drug Discovery Symposium held in late October. From 26 accepted posters, Ahmadi was one of four chosen to present in the lightning talk round where she won $500 for best presentation.

The symposium highlighted recent progress in the application of machine learning techniques to drug discovery and brought together researchers in the field working in applying machine learning to target validation, hit identification and optimization, clinical trial design, biologics, or other areas of drug discovery.

Ahmadi’s work, “A Physics-Informed Neural Network Framework for Drug Pharmacokinetic-Pharmacodynamic Model Discovery" investigates the world of scientific machine learning and its applications in drug discovery. A biomedical engineering Ph.D. student, Ahmadi introduces a physics-informed framework for parameter estimation and gray-box identification in drug discovery to help discover the partial missing physics.

“I'm incredibly grateful for this unique opportunity and extend my heartfelt thanks to the Broad Institute of MIT and Harvard, as well as my advisor Prof. George Karniadakis for his exceptional mentorship,” she said. “It was an incredible experience presenting to an audience of over 300 people in person and more than 1,000 online participants, making this event even more special.”

Ahmadi’s lightning talk has been posted on the youtube channel of the Broad Institute.