BUILDING THE FUTURE
OF QUANTAMENTAL
ANALYTICS
I'm an applied AI engineer focused on quantitative finance and agent systems. I build end-to-end trading infrastructure — research, backtesting, execution, and validation — and have led agentic products from concept to production.
Experience
Currently building Zen Trading's agentic quantamental platform — multi-factor ML/RL strategies, the Zentos CLI for external quant contributors, and LLM agents that orchestrate rather than trade. The bet is that agentic systems work best as a rigorous layer over deterministic models, not a replacement for them.
Previously at FedML, Alibaba Cloud PAI (federated learning & EAS deployment), and Tencent CV Lab (defect detection engineering).
Studied at Carnegie Mellon University (MSIT) and Queen Mary University of London & Beijing University of Posts and Telecommunications (BEng & BMgt).
Interests & Activities
Multimodality Application: Interactive Handwritten Math Formula — Using a reMarkable reader to capture handwritten math formulas and pairing it with the real-time voice API to explain what each formula is used for, making mathematical concepts more intuitive and accessible.
Incubating Math Education in the Agent Era: In the LLM era — when any text or line of code can be generated in seconds — I worry we're losing the meta-cognitive ability to reason about the world mathematically. Without that foundation, the upper layers of the software stack become fragile. If you're studying math or physics and curious how agents can help humans build stronger mathematical intuition (especially engineers), I'd love to chat.
Private Market Research: Integrated pre-IPO and private market tracking into my official project—wish someone could sponsor me a Crunchbase API!
📍 Based in Bay Area, California • Authorized to work in the United States (no H-1B sponsorship required)