Steven Zucker, PhD

Zucker's group bridges between theoretical models of information processing and machine learning, computational neuroscience, and computational vision. For behavior, they study the dynamic connectome in C. elegans, relevant to the Center for Neurodevelopment and Plasticity, in collaboration with the Yemeni laboratory at the University of Massachusetts. In vision, they consider questions from early to intermediate (cognitive) levels, using the mouse and primate as physiological models. The early vision project collaborates with experimental groups, the Field lab at Duke, which works on the retina, and the Stryker lab at UCSF, which works on the visual cortex. The analysis has resulted in a novel neural encoding manifold, on which each point is a neuron, and nearby neurons respond similarly in time to an ensemble of naturalistic and artificial stimuli. Such modeling, analysis, and collaboration are relevant to the Center for Neurocomputation and Machine Intelligence. The intermediate vision project relates to how humans could infer shape (3D information) from image information across lighting, material, and viewing changes using topological methods, as well as questions at the border between perception and cognition.

computational modeling ;  dimensionality reduction ;  manifold learning  

computational neuroscience ;  machine learning ;  vision  

Zucker is the David and Lucile Packard Professor of Computer Science, Professor of Biomedical Engineering, joint Professor of Statistics and Data Science, and a member of the Program in Applied Mathematics and the Interdepartmental Neuroscience Program. He arrived at Yale about three decades ago from McGill University and is fascinated by understanding how brains, bacteria, and biology work.