Quantitative Bioscience at the University of Tennessee

Social and Evolutionary Dynamics

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
	David Anderson Email	Anthropology	Eastern U.S. prehistoric and historic archaeology, development of cultural complexity, colonization and migration
	Alex Bentley Email	Anthropology	Culture evolution, computational social science
	Michael J. Blum Email	Ecology & Evolutionary Biology	Aquatic ecology, socioecology, sustainability, conservation biology
	Elizabeth Derryberry Email	Ecology & Evolutionary Biology	Behavioral and cultural evolution
	Nina Fefferman Email	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
	Todd Freeberg Email	Ecology & Evolutionary Biology and Psychology	Complexity of communicative signals
	Sergey Gavrilets Email	Ecology & Evolutionary Biology; Mathematics	Theoretical evolutionary biology, social and evolutionary dynamics
	Louis Gross Email	Ecology & Evolutionary Biology; Mathematics	Mathematical ecology. Director, NIMBioS; Director, The Institute for Environmental Modeling (TIEM)
	Christopher Strickland Email	Mathematics, Ecology & Evolutionary Biology	Mathematical ecology, addiction epidemiology, data-driven mathematical modeling, computational biomath

NIMBioS
1122 Volunteer Blvd., Suite 106
University of Tennessee
Knoxville, TN 37996-3410
PH: (865) 974-9334
FAX: (865) 974-9461
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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.