Network Systems Science and Advanced Computing

Christopher Kuhlman

  • Research Associate Professor
Chris Kuhlman headshot


Chris J. Kuhlman is a research associate professor in the Network Systems Science and Advanced Computing division. Kuhlman leads or supports projects in cyberinfrastructures, software systems and (hybrid) simulation tools development, human behavior during disasters, decision making, contagion control and optimization, models of human cooperation, and epidemiology. Kuhlman has more than 60 publications in computer science-related conferences and journals.

  • Discrete dynamical systems, modeling and simulation, distributed and high-performance computing, model building, social and network science, human behavior, and control of dynamics processes.

  • Virginia Tech, Computer Science, Ph.D., 2013
    Virginia Tech, Mathematics, M.S., 2013
    Virginia Commonwealth University, Computer Science, M.S., 2007
    University of Texas—San Antonio, Finance, M.B.A., 1997
    University of Illinois—Urbana, Mechanical Engineering, M.S., 1988
    University of Illinois—Urbana, Engineering Mechanics, B.S., 1987

  • Internship, Lawrence Livermore National Laboratory, Livermore, CA, Fall 2011

Selected Publications
Network Systems Science and Advanced Computing
Adiga A; Kuhlman C; Marathe M; Ravi S; Rosenkrantz D; Stearns R . Proceedings of the 31st AAAI Conference on Artificial Intelligence. 2018; :4630-4637
Network Systems Science and Advanced Computing
Kuhlman C; Mortveit H . Journal of Cellular Automata (JCA). Old City Publishing. 2015; 10(3):161-193
In the News
Biocomplexity Institute News

What do hip-hop and hurricane evacuations have to do with network science? High school students learned the answers to that and more in an inaugural series of network science lectures, given by University of Virginia Biocomplexity Institute researchers Chris Kuhlman, Dustin Machi and S.S. Ravi at the annual Achievable Dream Summer Program.

Network Science

The University of Virginia’s Biocomplexity Institute was recently awarded a five-year $4 million collaborative grant from the U.S. National Science Foundation (NSF) to build a self-sustaining cyberinfrastructure (CINES – pronounced “science”) to serve as an open-source, web-based repository for developing, trading, analyzing, and sharing network science resources.