Rahul G. Krishnan
Assistant Professor, Department of Computer Science and Temerty Faculty of Medicine
Rahul G. Krishnan is an assistant professor in the Department of Computer Science, and in Laboratory Medicine and Pathobiology within the Temerty Faculty of Medicine. He received a PhD from the Massachusetts Institute of Technology in 2020, as well as an MS from New York University and a BASc from the University of Toronto. After completing his PhD, Krishnan spent a year as a senior researcher with Microsoft Research New England. He was recently awarded a CIFAR AI Chair to further his research.
Krishnan’s work lies at the intersection of machine learning and health care. He is interested in developing new machine learning models and algorithms from clinical data with a view to building tools that will assist clinicians in making challenging decisions about patient health. Krishnan is particularly interested in a class of models known as deep generative models. These blend recent successes in deep neural networks with those from classical statistical models known as Bayesian networks.
Krishnan has applied his family of models to the solution of a diverse variety of problems. These include creating recommender systems, predicting false alarms in intensive care units, and modelling the progression of biomarkers in multiple myeloma. More recently, he has been developing models that leverage auxiliary information to make better, more robust predictions in high-stakes scenarios. Just as clinicians employ contextual clues when learning about patient conditions, Krishnan seeks to build new learning algorithms for deep generative models that can make safe, reliable and eventually causal predictions by leveraging contextual information.