Gal Chechik

Learning systems lab Computer science department Bar Ilan University See also my (Stanford webpage) Office: +972 (3) 531-7410 gal dot chechik at biu dot ac dot il

I am interested in learning in biological and artifical systems: brains and machines. My work focuses on developing large scale machine learning algorithms and data-driven models to analyze the structure and function of complex adaptive and biological systems.

Most recently, I am interested in learning to generalize from few samples to unseen combinations, and how this can be used to scale machine learning to understand and generate complex scenes.

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Gal Chechik is a Professor of Computer Science at Bar-Ilan University and a director of AI at NVIDIA, Leading NVIDIA research in Israel. His research spans learning in brains and machines, focusing mainly on deep machine learning for perception and reasoning.

In 2018, Gal founded the NVIDIA research group in Israel, and has been leading it since. Prior to that, he was a staff research scientist at Google working on machine perception and search. Gal earned his PhD in 2004 from the Hebrew University developing machine learning methods to study neural coding. In his Post-doctoral work at Stanford, he studied computational principles of molecular biology pathways. In 2007, he joined Google research, where he worked on various problems including large scale machine learning for perception and search. In 2009, he founded the learning systems lab at the Gonda brain research center of Bar-Ilan university, where he was appointed an full professor in 2019. Gal is the author of ~120 refereed publications, and ~50 patents, including publications in Nature Biotechnology, Cell and PNAS. His work won best-paper awards at NeurIPS and ICML, the world leading conferences in machine learning.