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Quantitative Bioscience at the University of Tennessee

Social and Evolutionary Dynamics

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Social and evolutionary dynamics are explored using mathematical models and computational approaches. The research draws from evolutionary biology, paleo-anthropology, evolutionary psychology, network science, non-linear economics, social psychology, social and political sciences, artificial intelligence, computer science, and new approaches to history and social evolution.

Visit the Center for the Dynamics of Social Complexity (DySoC) at NIMBioS.

Researcher Department Research Interests
 photo. David Anderson
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Anthropology Eastern U.S. prehistoric and historic archaeology, development of cultural complexity, colonization and migration
 photo. Alex Bentley
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Anthropology Culture evolution, computational social science
 photo. Michael J. Blum
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Ecology & Evolutionary Biology Aquatic ecology, socioecology, sustainability, conservation biology
 photo. Elizabeth Derryberry
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Ecology & Evolutionary Biology Behavioral and cultural evolution
N. Fefferman. Nina Fefferman
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Ecology & Evolutionary Biology; Mathematics; Director, Math Modeling Consulting Center Self-organizing complex systems, mathematical and computational models of problems in epidemiology, evolutionary and behavioral ecology, conservation biology
 photo. Todd Freeberg
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Ecology & Evolutionary Biology and Psychology Complexity of communicative signals
S. Gavrilets. Sergey Gavrilets
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Ecology & Evolutionary Biology; Mathematics Theoretical evolutionary biology, social and evolutionary dynamics
L. Gross. Louis Gross
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Ecology & Evolutionary Biology; Mathematics Mathematical ecology. Director, NIMBioS; Director, The Institute for Environmental Modeling (TIEM)
C. Strickland. Christopher Strickland
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Mathematics, Ecology & Evolutionary Biology Mathematical ecology, addiction epidemiology, data-driven mathematical modeling, computational biomath



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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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