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.

CV  /  Email  /  Google Scholar  /  LinkedIn

profile photo

Research Interest

I study how to make synthetic data more reliable and effective for scaling AI training pipelines. My work challenges the assumption that even well-structured synthetic data is always beneficial, showing that, without careful integration and diagnostics, it can degrade performance or distort learning dynamics. I develop methods for structured data augmentation, failure analysis, and algorithmic repair to make synthetic data more trustworthy. Recent projects include empirical studies exposing structural flaws in model-based RL pipelines built on synthetic rollouts, time-symmetric data augmentation in sequential decision-making problems, and ongoing development of diagnostic tools for out-of-distribution detection using diffusion models, aimed at identifying when synthetic data distributions diverge from trusted real-world contexts.

News


Design and source code adapted from here