Gal Chechik

Gal Chechik.

The computational neurobiology lab
The Gonda brain research center
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 complex scenes.


MY LAB  |  PUBLICATIONS  |  CV  |  CODE  |  DATA  |  BOOK


Bio:
Gal Chechik is an Assoc. Prof at the Gonda Brain research institute. His research spans learning in brains and machines, including large-scale learning algorithms for machine perception, and analysis of representation and development of mammalian brains.

Gal earned his PhD in computational neuroscience in 2004 from the Hebrew University of Jerusalem studying mammalian neural coding, after an MSc in computer science (summa cum laude) at TAU. He then worked at the CS dept of Stanford as a research associate with D. Koller, studying computational principles regulating the response of molecular pathways to extrenal changes. In 2007 he joined Google research (California) as a senior research scientist, developing large scale machine learning algorithm for machine perception. Since 2009, he heads the computational neurobiology lab at the Gonda center of Bar Ilan university, and was appointed an associate professor in 2013. Gal is the author of ~75 refereed publications, including publications in Nature Biotechnology, Cell and PNAS. He was awarded a fullbright fellowship, a complexity scholarship and an Alon fellowship.