// Hello, world! I'm
A Psyduck from UC Berkeley 🐥 — waddling through data, building ML models, and occasionally suffering from a statistical headache. Passionate about turning messy numbers into beautiful insights.
I'm a second-year M.A. Statistics & Data Science student at UC Berkeley, working at the intersection of machine learning, large language models, and quantitative finance. My path began at Zhejiang University, where I graduated with honors in Economics (Advanced Class).
As an AI Developer at Monolithic Power Systems, I build production LLM systems — a self-hosted document-translation platform, a SEC EDGAR MCP server that surfaces filings inside Claude, and an agentic slide-generation tool. My research at Berkeley spans retrieval-augmented generation and the pragmatics and calibration of LLM/VLM agents.
Earlier, internships at leading Chinese financial institutions grounded me in gradient-boosting models, network analysis, and alpha research. I thrive on turning messy data into rigorous, interpretable systems.
I'm actively looking for AI, machine learning, and quantitative research roles. Whether you have a full-time opportunity, an internship, or just want to chat about interesting problems — my inbox is always open.
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