Pioneering the Intersection of Machine Learning, Statistics, and Genomics
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Massachusetts Institute of TechnologyBorn in Switzerland in 1983, Caroline Uhler has risen to become a leading figure in statistical machine learning and computational biology. Currently serving as the Andrew (1956) and Erna Viterbi Professor of Engineering at MIT and Director of the Eric and Wendy Schmidt Center at the Broad Institute, her journey began with multiple degrees from the University of Zurich - a BSc in Biology, MSc in Mathematics, and MEd in High School Mathematics Education. Her path changed when she discovered algebraic statistics through Professor Bernd Sturmfels, leading her to pursue a Ph.D. in Statistics at UC Berkeley, which she completed in 2011. After postdoctoral positions at the University of Minnesota and ETH Zurich, followed by three years as an assistant professor at IST Austria, she joined MIT's faculty in 2015. Her groundbreaking research combines machine learning, statistics, and genomics, with particular focus on causal inference, representation learning, and gene regulation. Her exceptional contributions have earned her numerous prestigious honors, including the NIH New Innovator Award, Simons Investigator Award, NSF CAREER Award, Sloan Research Fellowship, and election to the International Statistical Institute. She is also a SIAM Fellow and IMS Fellow, while maintaining her passion for teaching and mentoring students at MIT. Most recently, her work has expanded to include developing machine learning methods for drug repurposing, including applications for COVID-19 treatment.