Prof. Gal Chechik
Machine Learning and Generalization from Few Examples
CV
Prof. Chechik is a Professor of Computer Science at Bar-Ilan University and the founder and director of the NVIDIA AI Research Center in Israel (established in 2018). He previously served as a Senior Staff Research Scientist at Google and completed his PhD at the Hebrew University followed by a post-doctorate at Stanford. He has authored approximately 160 publications and 60 patents, including in journals such as Nature, Cell, and PNAS, and has received Best Paper Awards at NeurIPS and ICML.
Research
Machine Learning and Generalization from Few Examples
Artificial Intelligence is built on machine learning technology – yet machines learn very differently from humans. While people can recognize an object from a single glance, even when viewed from a new angle, posture, or lighting, an AI system requires numerous examples to achieve the same capability. Prof. Gal Chechik asks: How can we teach machines to generalize from just a few examples, much like the human brain?
Prof. Chechik’s lab develops large-scale machine learning algorithms to analyze complex systems – both biological and artificial. The lab focuses on generalizing from few examples to novel situations and expanding the frontiers of machine learning toward understanding and creating complex scenes.
Core Research Areas:
Few-Shot Learning
Deep Learning
Computer Vision & Representation Learning
Generative Models
Learning in Brains and Machines
Research Character:
Theoretical–Applied - Developing advanced algorithms and models alongside real-world functional systems, in collaboration with NVIDIA Israel.
Career Horizons:
Graduates of the lab hold key positions at the forefront of technology:
Industry: Data scientists, AI researchers, and research team leads in top global technology companies.
Academia: Independent researchers and faculty members at universities in Israel and abroad.
Entrepreneurship: Founders of tech companies and R&D leaders in computer vision, NLP, and generative models.
Publications
Last Updated Date : 06/08/2026
