About

I spend my time thinking about how to use data and empirical analysis to drive better decision making. In the last few years, that idea has been extended to artificial decision-makers, not just human ones.

Over the last decade I’ve applied that interest across healthcare, finance, and government.

Work

Berkeley Research Group

  • I worked on building economic damages models for drug pricing disputes and pharmacy benefit managers, synthesizing corporate data dumps and contract covenants.
  • I taught myself to code in Python and Ruby and after working on a case for CDS price fixing, decided I wanted to try my hand at more forward looking models in finance.

Hudson River Trading

  • I built software for automating the tracking and pricing of our settlement obligations, consolidated net capital, and compliance screens. I got to try my hand at running the settlement book as well.
  • After working with traders for a few years, I saw that deep technical depth offers freedom to work on larger, more valuable problems.

Stanford

  • Coursework in statistical and machine learning led directly to many opportunities to apply it.
  • LLM research with SAIL, building ML product solutions with MBA students, economics research into wage effects of robotic automation, predictive algorithms for blood transfusion demand at Stanford Hospital, statistical consulting for other departments.

C3.ai

  • Quick internship building GovTech during the pandemic, using state space models to predict local infection trajectories and economic effects.

Primer AI

  • A full time role building GovTech AI products for national security agencies.
  • Trained and deployed models for entity recognition, relation extraction, and semantic search to solve knowledge discovery problems in large unstructured datasets.
  • When the ground under AI shifted in 2022, I left to explore the endless new opportunities created.

HighRoad AI

  • Founded a company bringing AI to private investors in CRE. Built the full stack product myself and screened deals for funds with $10B+ under management.
  • Working at the frontier, exploring problems in AI traceability and trust, self-assembling software, and continuous learning loops.

Now

Consulting with funds and startups building with AI. More detail can be found here →.