Trevor Chow
I am interested in online learning: taking imperfect information and make better decisions in real-time.
I work on one instance of this, browser agents, at Moonglow (YC S24), and write about two others, AI and financial markets, at Bunnyhopping (supported by EV).
My background is in mathematics at Stanford (esp. numerical methods), where I taught models to learn at inference time with Hazy Research Lab.
I’ve also worked on trading index options at Optiver, and building market making algorithms for the SPX complex that react to orderbook microstructure dynamics.
When I was younger, I was a King’s Scholar at Eton College and was active in the British competitive mathematics and debating circuits.
Beyond work, I split my time between ski slopes, skydiving dropzones and the Eras Tour. Say hi!