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We use mathematical models and computer simulations to study a wide range of problems in population biology, animal behavior, and evolutionary theory. Our current research efforts are concentrated in two areas.
Information in biological systems.
How do living organisms acquire, store, and make use of information? How and why does communication evolve?
Together with evolutionary theory, I use mathematical game theory and the statistical theory of signal transmission in order to understand the flow of information in the natural world. I am particularly interested in the strategic aspects of communication: Why do organisms share information even when their interests conflict? Why do individuals share some pieces of information and not others? Why do signals take the forms that they do? Why don't cheaters exploit and undermine communication by sending deceptive signals? How does information flow through biological and social networks?
The ecology and evolution of infectious disease:
How do pathogens evolve and spread through populations? How do populations evolve in response to pathogen challenge?
In an age of emerging infectious diseases and of rapidly spreading antibiotic resistance, ecologists and evolutionary biologists have significant contributions to offer to medical research and practice. In order to anticipate and to contain disease spread and disease evolution, we need to understand the underlying population biology and population genetics of both pathogen and host. Conversely, through the wealth of available data and the rapidity of the pathogen evolution, infectious disease biology offers to population biologists an opportunity to observe evolution taking place in real time, and as such provides a rich set of study systems for biologists who are interested in the basic ecological and evolutionary principles. I am particularly interested in finding ways to use our understanding of ecology and evolution to better understand and ultimately prevent the appearance and spread of emerging infectious diseases such as SARS and H5N1 avian influenza (bird flu).
In addition to these two areas, I maintain an active program of research on the structure and economics of scholarly publishing. In addition our journal articles on the subject, our website Eigenfactor.org is devoted to ranking and mapping the structure of scientific communication.
Carl T. Bergstrom is a Professor in the Department of Biology at the University of Washington. Dr. Bergstrom's research uses mathematical, computational, and statistical models to understand how information flows through biological and social systems. His recent projects include contributions to the game theory of communication and deception, use of information theory to the study of evolution by natural selection, game-theoretic models and empirical work on the sociology of science, and development of mathematical techniques for mapping and comprehending large network datasets. In the applied domain, Dr. Bergstrom’s work illustrates the value of evolutionary biology for solving practical problems in medicine and beyond. These problems include dealing with drug resistance, handling the economic externalities associated with anthropogenic evolution, and controlling novel emerging pathogens such as the SARS virus, Ebola virus, and H5N1 avian influenza virus. He is the coauthor of the college textbook Evolution, published by W. W. Norton and Co., and teaches undergraduate courses on evolutionary biology, evolutionary game theory, and the importance of evolutionary biology to the fields of medicine and public health. Dr. Bergstrom received his Ph.D. in theoretical population genetics from Stanford University in 1998; after a two-year postdoctoral fellowship at Emory University, where he studied the ecology and evolution of infectious diseases, he joined the faculty at the University of Washington in 2001.