AI/ML researcher with 15+ years in software engineering, working on agentic systems and their labor-market impact. AI architecture across Commerce (BigCommerce, Feedonomics, and Makeswift). Previously 8+ years at Amazon Web Services. Contributor to emerging agentic AI standards.
A multi-regional task exposure analysis of emerging labor market disruption — 236 occupations across 5 US tech metros, extending Nobel laureate Daron Acemoglu and Pascual Restrepo's task displacement framework to handle agentic AI.
Top ~10% of IEEE's 400,000+ global membership. Requires demonstrated engineering excellence and community impact.
Peer reviewer at the World Congress on Computational Intelligence — IEEE's flagship AI and neural networks conference.
Judge, University of Washington Foster School of Business MBA Case Competition, March 2026.
Recognized for contributions to the general availability launch of Amazon Transform, a major AWS product.
Drawn to the problem of model integrity — how AI systems can be compromised silently, at the data layer or the inference layer, in ways that pass every standard quality check. The NIST AI 100-2 taxonomy frames this well: availability breakdown versus integrity violation. I am most interested in the integrity side. Currently reviewing adversarial ML research for IEEE WCCI 2026 IJCNN.
There is a state where thought dissolves into doing. Where the painter, the athlete, the scientist, and the soul are the same person. That state has a name. Krita.
Available for research collaborations, conference speaking, advisory roles, and media inquiries on agentic AI, enterprise AI strategy, and AI's labor-market impact. Reaching out as an independent researcher.