An interdisciplinary researcher at the intersection of machine learning, statistics, and biology, Uhler develops methods to extract mechanistic insights from different kinds of biological data.
Caroline Uhler named core member of Broad Institute
The Broad Institute of MIT and Harvard has named Caroline Uhler as a core institute member.
Uhler currently co-directs, along with Anthony Philippakis, the Eric and Wendy Schmidt Center, which partners with the Broad community as well as the broader scientific ecosystem to bridge machine learning and biology.
“Caroline is a visionary leader who understands the potential of machine learning methods to transform biomedical research,” said Todd Golub, director of the Broad. “We are thrilled that she will have an even larger role at the Broad.”
“This is an incredible moment in time, one where we are seeing the convergence of the life sciences and the data sciences. Caroline is one of those rare individuals that has real expertise in each, and she is able to translate across them and make deep connections between them. It’s an honor to work with her on the Eric and Wendy Schmidt Center,” said Anthony Philippakis, who is also an institute member and chief data officer at the Broad.
Core institute members have their primary laboratories at the Broad Institute and have academic appointments at MIT, Harvard University, or one of Harvard’s primary teaching hospitals. They are deeply engaged in the intellectual life of the Broad and help set the institute’s scientific direction.
A tenured associate professor in the Department of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society at MIT, Uhler is interested in gaining mechanistic insights to understand gene regulation in health and disease. Her group has pioneered methods for learning causal relationships from observational and perturbational single-cell datasets and integrating data acquired at different time points in a biological process.
She will continue developing machine learning and statistics methods to bridge the gap between predictive and causal modeling by integrating different data modalities including transcriptomics, proteomics, and structural information.
“I’m honored and excited about the opportunity to deepen my engagement with the Broad as a core institute member,” Uhler said. “I’m really looking forward to even deeper collaborations with the Broad’s scientific community to expand the interface between machine learning and the biomedical sciences with the goal of bringing machine learning to bear on biological discovery as well as making biology a key driver of foundational discoveries in machine learning."
Uhler holds an M.Sc. in mathematics, a B.Sc. in biology, and an M.Ed., all from the University of Zurich. She obtained her Ph.D. in statistics from UC Berkeley and then spent three years as an assistant professor at IST Austria before joining the faculty at MIT. She has received multiple prestigious career prizes including a Simons Investigator Award, a Sloan Research Fellowship, a Sofja Kovalevskaja Award, and an NSF Career Award.
To learn more about Caroline Uhler’s research, visit her lab page.