I build software systems that learn from use.
Right now my main focus is Bountiful Garden, a neighborhood harvest-sharing network that turns backyard abundance into real community. I'm also building OpenClawBrain, a native OpenClaw context-engine plugin that combines lossless transcript memory, a learned routing graph, replay-gated packs, and decision traces. Pelican is a private research system for autonomous options trading.
OpenClawBrain front doors: site · GitHub repo
ML Engineer at Instacart. PhD Economics, UCLA. BA Statistics & Economics, UC Berkeley.
Your neighbor's Meyer lemon tree dropped 200 lemons last week. You want six. Bountiful is the bridge — post your harvest, browse what's ripe nearby, and grab it off the porch. A farmers' market that never closes, where every stall is someone on your block.
A learned retrieval brain for OpenClaw. The agent keeps lossless transcript memory, learns seed and traversal choices from human/self/scanner/teacher signals, and serves only replay-gated immutable packs. TypeScript, open source.
A research system for autonomous options trading. Pelican watches the market, builds its own features, trains fresh models, and sizes positions — all without a human in the loop. Private infrastructure; notes available on request.
Machine Learning Engineer
At Instacart I build production ML systems that make real-time decisions at scale across inventory, promotions, and ads. Before that I did a PhD in economics at UCLA, where I spent years thinking about incentives, learning, and dynamic systems.
I'm especially interested in conversations about agent infrastructure, applied ML systems, and local-first product design.