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Research & Work
- I study how AI models become infrastructure—what gets adopted, what gets ignored, and how this shapes the future of intelligence
- My background is in applying ML and data to commercial systems at LinkedIn, Walmart, and Jet.com. I’ve advised senior leadership and led teams in product development and monetization, and recently lectured in Wharton's machine learning application curriculum, focused on tradeoffs between rule-based and ML systems in mitigating online price wars
- Today, I focus on the interface between frontier models and adoption: how data curation shapes reasoning, how infrastructure enables use, and how incentives drive deployment. I write about funding patterns, usage metrics, and the emerging economics of AGI
Personal
- I live in San Francisco
- Writers I admire include Noah Smith, Nick Bostrom, and Immanuel Kant. I enjoy science fiction films which provoke thoughts about the complexities of human life, such as The Three-Body Problem and The Prestige
Interests & Personal Philosophy
- Data: I believe the demand for high-quality training data is underestimated, and we will see the rise of data brokerage markets for AI
- Compute: Compute will drive not only decisions on what should be built, but what actually ships
- AI Research: I follow work on alignment and interpretability research
- Application: I'm tracking how core research labs vs. independent entities will faire in scaling real-world commercial adoption
- Life: I believe that your environment—especially your social and informational networks—shapes who you become more than your conscious choices do. What feels like “intentionality” is often just the emergent effect of subtle, repeated training signals from the people and structures around you