Ila Fiete is an associate professor in the Department of Neuroscience at the University of Texas at Austin (UT Austin). Fiete’s interests are focused on using computational and theoretical tools to better understand the dynamical mechanisms and coding strategies that underlie computation in the brain. Her recent focus is on error control in neural codes, on rules for synaptic plasticity that enable neural circuit organization, and on questions at the nexus of information and dynamics in neural systems, to understand how coding and statistics fundamentally constrain dynamics, and vice-versa.
Fiete obtained her Ph.D. in 2004 at Harvard University in the Department of Physics, while doing her thesis research in theoretical and computational neuroscience in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology under the guidance of Sebastian Seung. She was a postdoctoral fellow at the Kavli Institute for Theoretical Physics at the University of California, Santa Barbara, from 2004 to 2006. During this time, she was also a visiting member of the Center for Theoretical Biophysics at the University of California, San Diego. Fiete subsequently spent two years at the California Institute of Technology as a Broad Fellow in Brain Circuitry. In 2008, she joined the University of Texas at Austin as an assistant professor in neuroscience. She has taught courses in introductory neuroscience, neural network theory and computational neuroscience, and quantitative methods in neuroscience at the graduate and undergraduate levels, and has received teaching awards as a graduate teaching fellow at Harvard University and from the College of Natural Sciences, UT Austin.
Fiete has been an Alfred P. Sloan Foundation Fellow, a Searle Scholar, a McKnight Scholar, and an Office of Naval Research Young Investigator. She is currently a Howard Hughes Faculty Scholar and a fellow in the Center for Learning and Memory at the University of Texas at Austin.