A three-person team spanning theory to metal — the mathematics of signals and frames, through statistical machine learning, foundation model evaluation and formal methods, down to embedded systems, server kernels and robot autonomy. Four co-authored papers between us, in harmonic analysis, concurrent program verification, and signal analysis.

AI Applied Scientist, Amazon · Seattle, WA
Applied mathematician and AI scientist. Six-plus years building and evaluating machine learning systems at Amazon, Microsoft, Meta, and PNNL. LLM and agentic systems, foundation model post-training, reinforcement learning, adversarial robustness, and uncertainty quantification.
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Professor of Applied Mathematics, UMD · College Park, MD
Professor in the Department of Mathematics and the Applied Mathematics, Applied Statistics and Scientific Computation programme at the University of Maryland, which he currently directs. Research in harmonic analysis and its applications to engineering and computer science, particularly statistical signal processing and machine learning.
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AI Software Engineer, AWS · Austin, TX
Software engineer across the full stack of the machine. Five-plus years shipping production systems at AWS, Google, Nauticus Robotics, Sylphase, AFRL, and Leidos — server kernels, GNSS receivers, subsea robot autonomy, and LLM agents for enterprise supply chain.
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