IACS seminars are free and open to the public; no registration required. Lunch will not be provided.
ABSTRACT: Activity patterns of neural populations in the brain constitute representations of sensory stimuli and internal states. The nature of these representations and how they are learned are key questions in neuroscience. In this talk, Dr. Pehlevan will describe his research group’s efforts in building a theory of sensory representations as feature maps leading to efficient function approximation. Dr. Pehlevanwill also describe efficient and biologically-plausible learning algorithms of how the brain may learn such representations, and discuss the applications of these algorithms to neuromorphic computing.
BIO: Cengiz Pehlevan is working towards uncovering the brain’s algorithms and their biological implementation. He explores applications of these algorithms to machine learning problems. In his research, Pehlevan uses mathematical techniques from a wide range of disciplines, including statistics, engineering and physics. He works in close collaboration with experimentalists.
Pehlevan holds a doctorate in physics from Brown University. He was a Swartz Fellow at Harvard University and a postdoctoral associate at Janelia Research Campus. Prior to joining SEAS, Pehlevan was a research scientist at the Flatiron Institute.