Built by two Ph.D researchers at the frontier of statistics, AI, and quantitative finance — united by the conviction that the future of investing is mathematical, autonomous, and intelligent.
Lin is a statistician and AI researcher passionate about combining advanced mathematics, Agent AI, and market intelligence to discover long-term alpha.
Her work sits at the frontier of high-dimensional statistics, large language model research, and quantitative finance — developing frameworks where autonomous AI agents, geometric signal extraction, and Kelly-optimal capital allocation converge into a unified investment intelligence.
VinePeak is Lin's embodiment of that vision: exploring the intersection of AI, high-dimensional modeling, and investment strategy to define the next generation of quantitative finance.
Fan is a mathematician and venture capital investor who brings elite academic pedigree and deep capital markets expertise to VinePeak. A graduate of Tsinghua University's top-tier School of Management — one of Asia's most prestigious finance programs — he combines rigorous quantitative theory with real-world investment strategy.
As a top-ranked venture capital investor, Fan has a proven track record of identifying asymmetric opportunities across technology and financial markets. His mathematical foundation in statistics and management science informs a disciplined, data-driven approach to capital allocation and portfolio construction.
At VinePeak, Fan bridges the worlds of institutional investment and cutting-edge quantitative research — bringing the strategic vision and capital markets fluency needed to translate mathematical frameworks into actionable alpha.
Two disciplines. One vision. A shared belief that the future of finance belongs to those who master mathematics and intelligence together.
Financial markets are complex adaptive systems. Winning in them requires not intuition, but rigorous probabilistic reasoning and high-dimensional modeling.
LLM-powered autonomous agents reading earnings, news, and filings in real time will define the next generation of signal generation — replacing manual research entirely.
Long-run wealth maximization demands Kelly-optimal sizing. Applied to high-dimensional embedding manifolds, it becomes the unified theory of AI-native portfolio management.
Interested in our research, investment strategies, or joining the team? We welcome conversations with traders, researchers, and investors who share our vision.