Instacart Ads Automated Bidding
Budget-based marketplace ads bidding, return estimation, pacing, simulation, and production rollout.
PhD Economics, UCLA · Member of Technical Staff, Applied Science at Coframe
Economics, machine learning, and decision systems.
I build production systems where a model has to make a real decision, leave enough evidence to audit it, and improve without outrunning its guardrails.
Work
The production marketplace systems come first. Current independent work carries the same discipline into agent memory, adaptive experimentation, neighborhood food, and local coordination.
Budget-based marketplace ads bidding, return estimation, pacing, simulation, and production rollout.
Causal targeting from experiment outcomes: expected incremental effect, budget allocation, and policy evaluation.
Item-store availability and fulfillment ML with noisy catalog, store, shopper, and operational signals.
Local, source-backed shared memory for Codex, Claude Code, OpenClaw, and other MCP clients. It retrieves bounded context from private history, expands exact sources on demand, and records whether the context actually helped.
A phone-first neighborhood marketplace for homegrown food. Neighbors can make a garden, post what is ripe, discover nearby harvests, message each other, and arrange a share or trade.
A working book about the system between generation and allocation: propose safely, assign traffic, log what happened, join outcomes, and decide what is worth learning next.
A trilingual, mobile-first pilot for finding players to join an already-booked Hong Kong tennis court, splitting the fee, and getting lawful availability alerts—without automated booking.
A collaboration system for turning ambiguous work into inspectable plans, evidence, and clean handoffs without hiding the reasoning that produced them.
A retrieval-first policy assistant that keeps source documents, jurisdiction, and privileged operations visible instead of answering from a generic policy-shaped memory.
An inspectable forecasting and decision dashboard built around calibration, uncertainty, and the difference between a model score and a decision worth taking.
Links
Straight to the useful stuff.