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Daniel SussmanAssistant Professor


Ph.D., University of Illinois, Urbana-Champaign, 2012


View publications on Google Scholar.


Research area

Theoretical and computational soft condensed matter, disordered materials, machine learning

Research description

We use theoretical and computational techniques to study a wide variety of soft condensed matter systems both in and out of equilibrium. How do we explain the way disordered solids maintain their rigidity, and also how they fail? What can simple models of active matter teach us about the collective behavior of cells in dense tissue, or about how birds flock? We focus on the role of topology and topological interactions in protecting system behaviors even in the presence of strong fluctuations – this allows us to make strong predictions about how a system responds to perturbations even when using extremely simplified, coarse-grained representations. We employ data-science-driven techniques, working closely with experiments, to formulate precisely tests that can discriminate between different theoretical approaches.