Machine Learning for Discovery: Deciphering RNA Splicing Logic

Speaker

Prof. Oded Regev

Professor

Department of Computer Science

NY Courant Institute of Mathematical Sciences

Abstract

Recent advances in machine learning have led to powerful tools for modeling complex data with high predictive accuracy. However, the resulting models are typically opaque, limiting their usefulness in scientific discovery, bioengineering, and biomedical applications. Professor Regev will describe an interpretable-by-design machine learning approach capturing a fundamental cellular process known as RNA splicing. Our model provides a systematic understanding of RNA splicing logic, recapitulating and extending existing domain knowledge, and suggests underlying mechanisms. The talk will not assume any prior knowledge, and should be accessible to a broad audience.

Oded Regev is a Silver Professor in the Courant Institute School of New York University. He received his Ph.D. in computer science from Tel Aviv University in 2001, and was then a postdoctoral fellow at the Institute for Advanced Study. He is an ACM fellow, a recipient of the 2019 Simons Investigator Award and of the 2018 Gödel Prize, and was a speaker at the 2022 International Congress of Mathematicians. His main research areas include machine learning, molecular biology, theoretical computer science, and quantum computation.