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Much of Mr. Burke’s work has been in the application of mathematical and statistical modeling, multi-agent systems design, machine learning, and data visualization to problems in both the natural and social sciences, with a specialization in Bayesian techniques for reasoning under uncertainty.

His current research interests include belief functions (a generalization of Dempster-Shafer evidence theory), adversarial modeling, epistemic game theory, and computational techniques for reasoning about trust. He’s also fascinated by the promise of applying bio-inspired techniques to improve resiliency in complex systems.

Mr. Burke received an M.S. in Computer Science from the Oregon Graduate Institute, and a B.S.M.E. from Lehigh University.