About

  • I am a PhD student at NTU CCDS × Nanyang Business School. I am a member of the GIFTS, ADEFT, and RADIO labs, and Lab Coordinator for the I3 Lab. My main advisor is Prof. Will Cong (previously at Cornell), and I am co-advised by Prof. Sean Du, who leads NTU's RADIO Lab and was named to the Forbes 30 Under 30 Asia 2026 list in Healthcare & Science. I work on AI in finance, FinTech, quantitative finance, DeFi, real-world modeling, and social computing, especially AI ethics and accountability.
  • My current research interests beyond the core focus include explainable AI, market making, prediction markets, AI for game theory (Pokémon VGC), AI for education, and deep learning for protein design.
  • Outside research, I was Head of Quantitative at Arbital (Y Combinator 2026), leading a systematic portfolio across on-chain prediction markets and perpetual DEX market making (7-figure USD volume). My speciality: US egg market prices (USD/Dozen). Yes, that's a real thing.
  • Before starting my PhD, I was an AI Research Engineer at Singapore Management University's AI Multimedia Team, working on vision–language models, cultural AI, and ASEAN benchmarks with Prof. Chong-Wah Ngo.
  • My research journey started as a Research Intern at NTUST CITI Lab in Taipei under Prof. Shuo Yan Chou, working on RFMS and leading the outcome-economy research there.

Research interests

Finance & Economic AI. My research applies AI to quantitative finance, DeFi protocols, and economic modeling. This covers algorithmic trading and market microstructure, token mechanism design, and decentralized governance: the parts of finance where the questions are noisy, adversarial, and impossible to fully simulate.

Society, Ethics & Education. I think about how AI shapes and is shaped by social systems. Fairness, accountability, and how to design AI that opens up access to education and knowledge rather than closing it off. As autonomous hedge funds rise, accountability becomes a real question: who do we blame if something goes wrong?

Methods & Theory. On the methods side, real-world model evaluation, explainable AI, and game-theoretic approaches to multi-agent systems. I am drawn to settings where incentive alignment and strategic behavior matter as much as accuracy.