Ethan Weinberger
Machine Learning Scientist
insitro
ethan.weinberger@insitro.com
CV | Github | Google Scholar
I am a machine learning scientist at insitro, where I work on machine learning for drug discovery. I recently defended my PhD at the University of Washington, where I was fortunate to be advised by Su-In Lee. My goal is to help biologists tease out meaningful signals from large-scale datasets generated from high-throughput technologies. In practice, I have been working towards this goal mostly via the development of probabilistic models for analyzing single-cell omics data. My Ph.D work was supported partially by an NSF graduate research fellowship. A copy of my PhD thesis is available here.
In addition to my colleagues at insitro and the University of Washington, I have been fortunate to work with many brilliant scientists at other institutions. Towards the end of my PhD I had the pleasure of collaborating with colleagues from Joseph Ecker's group at the Salk Institute and Nir Yosef's group at the Weizmann Institute of Science. In 2022 I completed an internship at Genentech, where I was hosted by Aviv Regev and had a lovely time working with Romain Lopez and Jan-Christian Hütter.