
Hello, world! I’m a software engineer with a passion for search and developer infrastructure. I work on the developer platform team at Databricks and serve as an Apache Lucene committer and PMC member.
I strive to build software that “just works” – powerful and simple at once. I’m an open source enthusiast, and shared my experience joining the open source search community in Finding a home (and career) in the open source community.
Before Databricks, I worked at Elastic on the Elasticsearch search engine, as well as Sourcegraph and Palantir Technologies. I hold an M.S. in Computer Science and B.S. in Math from Stanford University.
Sourcegraph is a widely used code intelligence platform that helps enterprises work with large, complex codebases. I introduced semantic search to the Sourcegraph backend to power the popular Deep Search product.
Thanks to a new generation of models that can powerfully represent text as vectors, there’s been a surge of interest in vector-based semantic search. I led the introduction of vector search into Elasticsearch, and helped transform Lucene into a highly capable “vector database”.
Causal inference allows for determining the effect of an action on a larger system. The generalized random forests (grf) method combines insights from statistics and machine learning to enable causal analysis. I authored the grf software package, which won an inaugural Stanford Open Source Software prize for its research impact, quality, and dedication to open source principles.
⛰️ Backcountry cooking recipes. I’m an avid backpacker and enjoy finding creative ways to eat well outdoors.
🎵 Compositions. I love to write songs as gifts for family and friends.
🤓 Unicode. I’m the proud sponsor of Unicode characters μ and σ.