Joel Zylberberg Laboratory

Dr. Joel Zylberberg is a computational neuroscientist whose work bridges neuroscience and machine learning. His research focuses on understanding how the brain processes information about the world and how those representations are learned. By combining computational modeling with experimental data, Dr. Zylberberg aims to develop bio-inspired machine learning algorithms and improve our understanding of sensory systems like the retina and visual cortex.

Dr. Zylberberg's lab employs cutting-edge techniques in computational neuroscience, including deep learning frameworks and information theory, to uncover the principles of brain function and apply them to real-world problems in AI and medicine.