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About Me
Make things as simple as possible, but not simpler.
I develop algorithms and infrastructure for recursive self-improvement, especially around generative models, reinforcement learning, and software-engineering agents. Across research, engineering, business, and prioritization, I try to quotient out accidental detail, preserve the invariant, then build from there.
That is also how I think about GenAI from first principles.
Previously, I worked on core functions in leading technical spaces: ads recommendation at Meta, self-driving systems at Tesla Autopilot, and trading research at Kronos Research. I studied CS/math at Georgia Tech and NYCU.
Selected Highlights
- Contributor to slime and Harbor on RL training logic, agent integrations, and sandbox runtime fixes.
- Ranked top 0.56% among 96,000+ registrants in Google Code Jam 2020.
- 4.0/4.0 at Georgia Tech; A+ in Advanced Algorithms, Advanced Linear Algebra, Quantum Information and Computation, and Theoretical Aspects of Modern Cryptography.
- zkAlpha won ~US$9k across 7 prizes at ETHGlobal Paris (1,400 participants, 321 projects).
Beyond Work
I grew up in Taipei, Taiwan (Mandarin name: 林彥彤 / Yan-Tong Lin).
Outside work I have been spending more time on poker, health and fitness, competitive multiplayer games, guitar, and piano. A few traces: "Fight" acoustic guitar cover and an ETH CC Paris hacker house.