At Caterpillar, I have led five production AI initiatives spanning GenAI, forecasting, and enterprise data systems. I built Mino, an AI assistant that turns complex product and engineering documentation into grounded, traceable answers, and developed its ingestion, retrieval, evaluation, and CI/CD workflows. I also built machine-learning pipelines to forecast equipment repair timelines and supported dealer and customer forecasting for a portfolio representing approximately $930M in annual sales.
Previously, as a research scientist at UT Austin, I developed data-driven models for complex environmental and engineering systems. My work has resulted in a U.S. patent and six peer-reviewed publications. I enjoy taking ambiguous technical problems from initial exploration through production deployment while remaining hands-on and helping other engineers succeed.
