Abstract: In communities of living organisms, dynamic behavior is often driven by social interactions. Hydrodynamics simplifies the description of systems composed of many interacting constituents. While hydrodynamic models incorporating social interactions have been proposed, it is unclear the extent to which they describe real data. To address this issue, we combine tools from economics and statistical physics to construct and validate a hydrodynamic theory of social behavior. We show how to incorporate individual preferences within a hydrodynamic framework, verify our underlying hypotheses using neural networks, and apply the model to predict human residential dynamics across the United States.
Bio: Daniel S. Seara is a theoretical physicist studying the impact of intelligence and decision-making on the collective behavior of living and engineered systems, from micro-robots to societies. He is currently an Assistant Professor in the Department of Mechanical and Industrial Engineering at UIC and affiliate member at the NSF-Simons National Institute for Theory and Mathematics in Biology. Before joining UIC, he worked as a postdoctoral researcher at the James Franck Institute at the University of Chicago with Vincenzo Vitelli, studying the impacts of non-reciprocity in phase transitions and the transport properties of social systems. He received his PhD in Physics from Yale University in 2021, where he worked on problems in bioenergetics with Michael Murrell.
