Xaq Pitkow is associate professor of computational neuroscience at Carnegie Mellon University. He is a computational neuroscientist who develops mathematical theories of the brain and general principles of intelligent systems. He focuses on how distributed nonlinear neural computation uses statistical algorithms to guide actions in naturalistic tasks. He develops novel analysis methods validated on synthetic agents and collaborates closely with experimentalists to test theories on real data.
Pitkow was trained in physics as an undergraduate student at Princeton University and went on to study biophysics for his Ph.D. at Harvard University. He then took postdoctoral positions in the Center for Theoretical Neuroscience at Columbia University and in the Department of Brain and Cognitive Sciences at the University of Rochester. In 2013, he joined the faculty in the neuroscience department at Baylor College of Medicine, jointly appointed at Rice University in the Department of Electrical and Computer Engineering. After a decade there, he moved to Carnegie Mellon University, appointed in the Neuroscience Institute and the Department of Machine Learning by courtesy. He is currently associate director of the National Science Foundation’s AI Institute for Artificial and Natural Intelligence.
