Tavor Baharav
 |
Postdoctoral fellow |
Brief Bio
I am a third year postdoctoral fellow at the Eric and Wendy Schmidt Center at the Broad Institute, working with Rafael Irizarry. My research focuses on designing algorithms that learn from and adapt to data, with applications in computational genomics. Through a first-principles approach, I develop probabilistic models for biological data, algorithmic and statistical techniques for its analysis, and software implementations that enable practical use by the scientific community.
Currently, I'm primarily working on data integration problems, with an emphasis on T-cell repertoire analysis (immunology). Prior to this, I worked with Professor Julia Salzman to develop computationally efficient and statistically valid methods for analyzing raw sequencing data without a reference genome. I have also worked on adaptive algorithms for data science and machine learning problems using multi-armed bandits. My research borrows tools from optimization, information theory, and probability theory to design algorithms that are both theoretically grounded and practically efficient, for the new paradigms posed by high throughput sequencing data. Feel free to reach out if any of these topics interest you, I'm always happy to chat!
In 2023 I completed my Ph.D. in Electrical Engineering at Stanford University, where I worked with David Tse and Julia Salzman. At Stanford, I was gratefully supported by the NSF Graduate Research Fellowship and the Stanford Graduate Fellowship (SGF). Previously, I graduated from UC Berkeley, where I was fortunate to have the opportunity to work with Kannan Ramchandran on coding theory and its applications to distributed computing.
Contact
Email: “last name” at broadinstitute dot org
Room M1115, 75 Ames St, Cambridge, MA 02142