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Kanaka Rajan, Ph.D. is a Computational Neuroscientist and Assistant Professor at the Friedman Brain Institute at the Icahn School of Medicine at Mount Sinai in New York. Her research seeks to understand how important cognitive functions — such as learning, remembering, and deciding — emerge from the cooperative activity of multi-scale neural processes. Using data from neuroscience experiments, Kanaka applies computational frameworks derived from machine learning and statistical physics to uncover integrative theories about the brain that bridge neurobiology and artificial intelligence. Leveraging her unique expertise in the fields of engineering, biophysics, and neuroscience, Kanaka has pioneered computational approaches for understanding how the brain processes information, and how these processes become disrupted by neuropsychiatric diseases.

Dr. Rajan’s work has been recognized with several awards, including: The Lamport Basic Science Research Award, Young Investigator Award from the Brain and Behavior Foundation, Understanding Human Cognition Scholar Award from the James S McDonnell Foundation, Research Scholars Awards from the Di Sabato Foundation and the Dyal Foundation, and a Sloan Research Fellowship. Her work is supported by R01 funding from the National Institutes of Health (NIH) through the BRAIN Initiative, and FOUNDATIONS and CAREER awards from the National Science Foundation (NSF).

Prior to joining the faculty at Mount Sinai, Kanaka completed her postdoctoral work at Princeton University where she made significant contributions to the modeling of important neural processes, including feature selectivity and recurrent neural networks (RNNs). She received her Ph.D. at Columbia University.