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Work
- I study how intelligence behaves under pressure, how models drift when faced with emotional, social, or authoritative pressure. I’m interested in what these behavioral shifts reveal about alignment, safety, and the evolution of machine reasoning
- Before research, I built monetization and ML infrastructure at LinkedIn and Jet.com ($3.3B acq), where I learned how incentives shape both markets and models. I recently lectured in Penn’s machine-learning application course, sharing how firms weigh rule-based vs. ML features in online price war mitigation
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
- In my spare time, I invest in real estate, run, practice pilates, play piano, make coffee, and think about how humans (and models) reason about one another
- Native fluency in English, Mandarin & Cantonese; Limited professional fluency in Korean
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