Tatiana Sharpie
Professor · Computational Neuroscience
Salk Institute for Biological StudiesAbout
Dr. Tatiana Sharpie is a Professor at the Salk Institute for Biological Studies, holding the Edwin K. Hunt Chair. She leads the Computational Neurobiology Laboratory and Integrative Biology Laboratory, focusing on how the brain processes information despite dynamic biological changes. Her research integrates mathematical modeling, statistical physics, and information theory to study neural coding, sensory processing, and hyperbolic geometry in biological systems.
Education
- MS in Physics, National University of Ukraine, Kyiv
- PhD in Physics, Michigan State University
- Sloan-Swartz Postdoctoral Fellow, University of California, San Francisco
Sharpie's research explores invariant feature selectivity in sensory systems, neural adaptation to changing environments, and computational principles underlying information transfer in neural circuits. Her work has revealed hyperbolic representations in olfaction and spatial memory, with applications in brain-computer interfaces and neurological disorder diagnostics.
Her publications emphasize computational neuroscience, sensory processing, and machine learning methods applied to biological data. Recent work demonstrates strong trends in hyperbolic neural representations, sensory coding efficiency, and cross-species neural analysis.
Awards & Honors
- Prebys Research Heroes (2024)
- ASBMB DeLano Award in Computational Bioscience (2022)
- Fellow of the American Physical Society (2018)
- NSF CAREER Award (2013)
- McKnight Scholar Award (2009)
- Searle Scholar (2008)
- Alfred P. Sloan Fellow (2008)
She directs an active research group developing theoretical frameworks for neural computation and collaborates with the Kavli Institute for Brain and Mind. Her lab receives support from major foundations including WM Keck and Ray Thomas Edwards Foundation.
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