Causality, Perturbations, Gene Regulation, and Drug Repurposing
Caroline Uhler
February 23, 2022, Wednesday, 3:00 PM - 4:00 PM EST
An exciting opportunity at the intersection of single-cell biology and machine learning stems from the growing availability of large-scale perturbational data (drugs, knockouts, overexpression, etc.). I will present a framework based on causality and autoencoders that can integrate observational and perturbational data and discuss applications to learning gene regulatory networks as well as predicting the effect of new perturbations. We end by discussing how such a framework can be applied for drug repurposing in the current COVID-19 crisis.
Dr. Caroline Uhler joined the MIT faculty in 2015 and is currently the Henry L. and Grace Doherty associate professor in EECS (Electrical Engineering & Computer Science) and IDSS (Institute for Data, Systems and Society). She is also a core member of the Broad Institute, where she co-directs the newly-launched Eric and Wendy Schmidt Center. She is also a member of LIDS (Laboratory for Information and Decision Systems), the Center for Statistics, Machine Learning at MIT, and the ORC (Operations Research Center).

She holds an MSc in mathematics, a BSc in biology, and an MEd in mathematics education from the University of Zurich, and a PhD in statistics from UC Berkeley. Before joining MIT, she spent a semester in the "Big Data" program at the Simons Institute at UC Berkeley, postdoctoral positions at the IMA and at ETH Zurich, and 3 years as an assistant professor at IST Austria.

She is an elected member of the International Statistical Institute and a recipient of a Simons Investigator Award, a Sloan Research Fellowship, an NSF Career Award, a Sofja Kovalevskaja Award from the Humboldt Foundation, and a START Award from the Austrian Science Foundation.

Her research focuses on machine learning, statistics and computational biology, in particular on causal inference, generative modeling and applications to genomics, for example on linking the spatial organization of the DNA with gene regulation.