Brett Barkley

I am a PhD student at the University of Texas at Austin advised by David Fridovich-Keil.

I was previously employed by the Johns Hopkins Applied Physics Laboratory, where I worked on AI-based autonomy for aerospace systems.

I have an MS in Aerospace Engineering from the University of Maryland where I was a research assistant under Prof. Derek Paley and member of the Collective Dynamics and Control Laboratory (CDCL). My area of specialization was flight dynamics, stability, and control and my thesis proposed a scalable cooperative autonomy framework for multi-agent aerial reconnaissance.

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Research Interest

I am broadly interested in developing theory and algorithms that democratize performant deep reinforcement learning and enhance its sustainability when applied to robotic systems. Specifically, I believe this can be accomplished by integrating the three Rs of waste management (reduce, reuse, recycle) into the lifecycle of agent training, validation, and deployment. There are a number of open directions for this work, but I am particularly excited about the promise of this concept in generating generalizable AI at reduced computational cost.

News

• An Investigation of Time Reversal Symmetry in Reinforcement Learning was accepted to L4DC. (April 2024)
• Our work on AI for air-to-air combat was recently featured in The New Yorker. (Jan 2022)
• I was promoted to sub and full scale red autonomy lead for DARPA's Air Combat Evolution! (Sept 2020)
• Our work on AI for simulated 1v1 dogfighting as part of the DARPA AlphaDogfightTrials program was recently featured in the Economist, Fortune, Forbes, and Popular Mechanics. (Aug 2020)
• I joined the Intelligent Combat Platforms group at the Johns Hopkins Applied Physics Laboratory. (Apr 2019)

Design and source code adapted from here