Welcome to my personal page. I work on Model Measurement at OpenAI.
Previously, I was Head of Statistics Engineering at Eppo, an experimentation platform to empower the curious and entrepreneurial, where my time was roughly equally split between statistics, engineering and product work. Before that, I led the Core Representation Learning team at Stitch Fix. Our team built multiple recommendation systems to understand client preferences across dimensions such as style and size, forming the backbone of recommendations across Stitch Fix products.
I obtained my PhD at Stanford working with Ramesh Johari. My interests are at the interface of statistics, mathematics and computer science.
Experience
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OpenAI, Aug 2025 - Present
Member of Technical Staff working on Model Measurement.
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Datadog, May 2025 - Jul 2025
Staff Engineer following the acquisition of Eppo.
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Eppo, Nov 2021 - May 2025
As Head of Statistics Engineering, I led a team focused on combining statistical rigour with an intuitive product that empowers everyone to analyze experiments with confidence. Projects included work on sequential confidence intervals, CUPED, contextual bandits, geolift, and feature flagging architecture.
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Stitch Fix, Jun 2018 - Nov 2021
On the Algorithms team at Stitch Fix I have worked on a variety of machine learning, statistics and opimtization problems. These include
- Multiple algorithms based on latent embeddings: similar item search, diversifying recommendations, and generating outfits
- An experimentation framework to deal with spillover effects from inventory constraints
- Solving large scale optimization problems (distributed in PySpark, and with state of the art commercial solver)
- Creating a production system that serves Style Shuffle quizzes to clients in real-time
- Proposing, running, and analyzing multiple experiments
among others.
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Stitch Fix internship, Summer 2014 and Summer 2015
Stitch Fix is reinventing the retail industry through innovative technology. During my two summers on the Algorithms team at Stitch Fix, I worked on improving the recommendation engine that is used by stylists, along with tinkering on some side projects.
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HP Labs internship, Summer 2013
HP Labs is the research division of Hewlett-Packard. I worked under supervision of Rob Schreiber and with fellow intern Austin Benson on fault tolerance for the next generation of super computers. We demonstrated that we can make numerical methods resilient to silent errors at negligible cost by using mathematical properties of the methods. This has led to the publication of Silent error detection in numerical time-stepping systems.
Education
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PhD Computational and Mathematical Engineering, 2018
Advised by Ramesh Johari
Stanford University
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MASt Mathematics, 2012
University of Cambridge
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BSc Econometrics and Operations Research, 2011
University of Groningen