Quant researcher & agent engineer. HUST undergraduate building long-horizon research harnesses — persistent execution, environment feedback, auditable evaluation — and pointing them at markets and knowledge.

我是 Aidan H., 华中科技大学光电信息科学与工程本科在读。做量化研究（WorldQuant BRAIN）、AI Agent、Robotics。希望做有用的事情，或者有意思的事情。

• Agent engineering — building a persistent research agent: typed tool loops, MCP, SQLite-backed state, resumable long-running jobs (browser-close-proof).
• Quant research — WorldQuant BRAIN consultant. Testing factor hypotheses and automating the idea → formula → backtest → diagnose → refine loop.
• On-chain research — reconstructing Polymarket fill-level ledgers from Polygon to audit reported P&L and study market-maker behavior.
• Personal knowledge system — a local retrieval stack (Flomo / Notion / past sessions → FAISS, BGE embeddings) that treats my own notes as a queryable database.

• First principles — most problems collapse once you drop to the layer where they're actually defined.
• Ergodicity — time averages and ensemble averages are different things; a lot of "long-term" advice quietly assumes the ensemble.
• Evidence over adjectives — don't tell me it's "robust"; show me the number and the denominator.
• Doing things that are useful, or interesting — ideally both.

• Syna — 72-hour hackathon demo: Rokid smart glasses → Android journaling app. Real hardware, installable build, honest about what wasn't connected.

Most of my current work lives in private research repos (agent harnesses, on-chain audits). Reach out if you want to see something specific.

Python · TypeScript · C++ · SQL · Kotlin

PyTorch · XLA/TPU · pandas · NumPy · BigQuery

Agent: AI SDK · MCP · FastMCP · SQLite · Vitest · persistent workers

Retrieval: FAISS · sentence-transformers

sum999724@gmail.com — always up for talking markets, agent infra, or good books.