Amrut Nadgir

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Graduate Student

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Research Areas: Theoretical Neuroscience, Machine Learning

Computational Neuroscience Institute

My research focuses on studying optimal learning and decision making with realistic bounds. I expect animals to approximate the behaviors of optimal agents and seek to better understand exactly what constraints real animals obey and why. My explorations are done in a dynamic, continual learning setting to better describe situations faced in the real world. Before coming to UPenn, I worked on improving the state of the art in Molecular Dynamics simulations at D.E. Shaw Research. I have also worked on liquid-liquid phase separation experiments, atomic molecular optics experiments and recurrent neural network models of the brain while getting an undergraduate degree in physics at UC Berkeley.

Selected Publications

SARS-CoV-2 nucleocapsid protein forms condensates with viral genomic RNA SILIA: Software implementation of a multi-channel, multi-frequency lock-in amplifier for spectroscopy and imaging applications