I am a senior data scientist and AI generalist based in the Bay Area. I work on applied AI and data science problems where useful models depend on reliable data, clear measurement, and practical judgment.

I like the messy middle of applied AI: understanding the data, building useful models, measuring whether they work, and making them fit real workflows. My work draws from machine learning, experimentation, optimization, analytics, scientific computing, and the business context around the decision.

Before my current role, I spent years in research-heavy environments: first through a PhD in Physics at Purdue University, and later as a Senior Scientist at MemComputing.