Summary
Heng Fun is a founder and machine learning leader with a decade of experience building production ML systems and quantitative trading strategies, blending deep learning research with hands-on engineering. He has led LLM and agent initiatives for monetization at ByteDance, scaled web‑scale retrieval and ranking at Amazon, and architected HFT strategies as a quantitative researcher that helped deploy a fully invested $25M fund. His research background spans NLP, speech, memory-augmented networks, graph neural nets and differentiable computers, informed by an AI master's from USI and research roles at IDSIA and NNAISENSE. Comfortable at the intersection of research and markets, he pairs rigorous statistical methods and CFA-informed equity research experience with product-facing ML execution. Based in Seattle, he is currently building a stealth startup after participating in a16z Speedrun, bringing both startup grit and institutional-scale engineering discipline. A subtle throughline in his career is shipping research into revenue — from trading alpha to ad-targeting LLMs.
10 years of coding experience
12 years of employment as a software developer
Bachelor of Arts (BA) Economics Statistics, Bachelor of Arts (BA) Economics Statistics at University of Washington
Master's Degree in Computer Science - Artificial Intelligence, Master's Degree in Computer Science - Artificial Intelligence at USI Università della Svizzera italiana
English, Chinese, Chinese, Spanish