Tatyana Sharpee

Tatyana Sharpee is a Professor at the Salk Institute for Biological Studies, where she leads the Computational Neurobiology Laboratory. She holds the Edwin K. Hunter Chair and is affiliated with the Crick-Jacobs Center for Theoretical and Computational Biology and the Center for Theoretical Biological Physics at UCSD. Her research focuses on understanding how the brain processes information despite constant changes in its components and environment.

Dr. Sharpee's research interests center on computational principles of sensory processing, particularly how the brain creates robust representations of the external world. Her work integrates methods from statistical physics, mathematics, and information theory to study neural coding in vision, audition, and olfaction. She has made significant contributions to understanding how neural feature selectivity is shaped by natural stimuli statistics and how invariant representations are achieved despite neural variability.

Her recent publications reveal groundbreaking discoveries in odor perception (structured by a hyperbolic metric similar to Pringles potato chips), visual processing (how neurons combine selectivity for shape and texture), and theoretical frameworks for understanding neural coding. Her lab's work on Maximally Informative Dimensions has revolutionized how scientists analyze neural responses to complex stimuli.

• 2024 Prebys Research Hero
• 2022 Delano Prize in Computational Biology from ASBMB
• American Physical Society Fellow, 2018
• National Science Foundation Career Award, 2013
• WM Keck Foundation Research Excellence Award, 2009
• 2009 McKnight Scholar Award
• Ray Thomas Edwards Foundation Career Award, 2008
• Alfred P. Sloan Research Fellow, 2008

Dr. Sharpee mentors numerous graduate students and postdoctoral fellows, and her lab develops open-source computational tools widely used in neuroscience. Her research has significant implications for understanding neurological disorders including autism, Alzheimer's disease, schizophrenia, depression, and anxiety, with potential applications in brain-machine interfaces and novel treatments for sensory disorders.