Dr. Grant Rotskoff

Biography

Grant Rotskoff studies the nonequilibrium dynamics of living matter with a particular focus on self-organization at the molecular and cellular scale. His work involves developing theoretical and computational tools to probe and predict the properties of physical systems driven away from equilibrium. His research interests include characterizing and designing physically accurate machine learning techniques for biophysical modeling. Prior to his current position, Grant was a James S. McDonnell Fellow working at the Courant Institute of Mathematical Sciences at New York University. He completed his Ph.D. in Biophysics at the University of California, Berkeley, supported by the NSF Graduate Research Fellowship. His thesis developed theoretical tools for understanding nonequilibrium control in small, fluctuating systems encountered in molecular biophysics. Grant emphasizes the dynamics of mesoscale biophysical assembly response, applying machine learning techniques for dimensionality reduction of physical models, and developing methods for nonequilibrium simulation, optimization, and control, addressing key technical challenges in the theory of active biomaterials.

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