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The main goal of the CCVL (Computational Cognition, Vision, and Learning) research group is to develop mathematical models of vision and cognition. These models are intended primarily for designing artificial (computer) vision systems. Learning is required for extracting knowledge from data. Practical applications include vision for the disabled. These models also serve as computational models of biological vision which can be tested by behavioral methods and, in collaborative projects, with invasive, and non-invasive neuroscience techniques. We also study how humans and animals perform cognitive tasks such as learning and reasoning. In addition, we also use machine learning for interpreting medical images and studying brain function.

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Jun 16, 2026
Jieneng Chen Featured in Scientific American

CCVL alumnus Jieneng Chen was profiled by Scientific American as a young scientist creating AI...

Jieneng Chen Featured in Scientific American
May 27, 2026
Yuille Team Receives 2026 ICBS Frontiers of Science Award

Congratulations to Alan Yuille and collaborators Liang-Chieh “Jay” Chen, George Papandreou, Iasonas Kokkinos, and Kevin...

Yuille Team Receives 2026 ICBS Frontiers of Science Award
Mar 11, 2026
Eight papers accepted by ICLR 2026

We have eight papers accepted to ICLR 2026! Congratulations to everyone involved! The full publication...

Eight papers accepted by ICLR 2026
Mar 11, 2026
Eleven papers accepted by CVPR 2026

We have eleven papers accepted to CVPR 2026! Congratulations to everyone involved! The full publication...

Eleven papers accepted by CVPR 2026