Xaq Pitkow received a Ph.D. in biophysics from Harvard University in 2006. He then completed postdoctoral research at 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 took a position as an assistant professor jointly at the Baylor College of Medicine in the Department of Neuroscience and at Rice University in the Department of Electrical and Computer Engineering.
Professor Pitkow is a theoretical neuroscientist who aims to understand the principles that account for what the brain computes and why it computes this way. This research uses theoretical tools from mathematics, physics, statistics and computer science to understand the complex neural circuitry of the brain. For instance, three simple principles explain many findings in neuroscience: the brain looks for change, weighs the uncertain, and is deeply nonlinear. These three principles suggest how to extract actionable information from a dynamic world (look for the changes) that is filled with ambiguity (weigh the uncertain) and confounded by complex interactions between objects (untangle the sensory inputs using a deep nesting of nonlinear transformations). Professor Pitkow applies these general concepts primarily to sensory systems, especially vision. His results include explanations of how our brain can unblur our vision even as we constantly move our eyes, how visual signals are optimized for the capacity of our optic nerve and how the structure of our cortex is matched to the structure of natural images. In developing his mathematical theories of the brain, Professor Pitkow provides testable predictions for his experimentalist colleagues and helps them interpret the complex data that emerge from neuroscience experiments.