nina .h. fefferman AT


447 Hesler Biology Building
University of Tennessee, Knoxville
Knoxville, TN 37996

Curriculum Vitae

Current Positions
Professor University of Tennessee, Knoxville

Department of Ecology and Evolutionary Biology & Department of Mathematics

The National Institute for Mathematical and Biological Synthesis (NIMBioS)

Research Focus
Self-Organizing Complex Systems, Mathematical and computational models of problems in epidemiology, evolutionary and behavioral ecology, and conservation biology

Nina H. Fefferman, PhD

Principal Investigator

I am interested in the application of mathematical and computational models to biological systems, especially those systems created and governed by the voluntary collaboration of many independent individuals. In my research, I work on a broad variety of systems, both in my own lab and in collaboration with others at many different institutions.

My research usually falls into one or all of three categories: Epidemiology, Evolutionary & Behavioral Ecology, and Conservation Biology. I am interested in the effects of animal behavior, ecology and infectious disease epidemiology on one another. I model disease in both human and animal populations, and am interested in how disease and disease-related behavioral ecology can affect the short-term survival and long-term evolutionary success of a population. Some of my current projects focus on the modeling of endangered populations of tortoises to determine effective courses of management, social insect populations and their susceptibility to pathogens based on their behavior and nesting ecology, the effects of stress on populations in fluctuating environments, and how best to maintain human societal infrastructure in the face of pandemic disease.

Mathematically, I am interested in Complex Systems: the mathematics of studying the conclusions or outputs of systems where each component is relatively simple (governed by a small set of logical rules), but when you put a lot of them together they react to each other and create highly organized systems and incredibly complex behaviors. Not only are these systems fascinating and beautiful by themselves, but they have direct applications to the types of biological problems mentioned above. For example, in social insect biology, individual honey bees forage for nectar and communicate information about their foraging success to foraging sister bees, but each bee decides independently for herself where to go to next and somehow, as a whole, the nest forages very (mathematically) efficiently!