David Burke

Research Lead, Machine Learning

In addition to my role as lead of the Machine Learning Research Program, I also lead Galois’ Blue Sky initiative. The long-term viability of Galois requires innovation, and Blue Sky is one of the key vehicles inside Galois for enabling that innovation to happen. Our primary concern is ensuring that the Galois culture embodies creative, long-term, disruptive thinking.

Linus Pauling once said, “The best way to get a good idea is to have a lot of ideas,” and it’s the job of Blue Sky to encourage and nurture them.


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.