We’re combining modern computational geometry, high-fidelity physics simulations, and machine learning on large-scale manufacturing data to generate plans for execution in our automated factory.

We built Exactrics in order to improve the online clothes shopping experience. With just a few photos, Exactrics would enable you to search, filter, and compare clothing by both look and *fit* while you shop online.At Exactrics, I was responsible for all of our back-end infrastructure, including:• A pipeline for converting sets of smartphone photos into millimeter-precision clothing scans • Custom fit-search, look-search, and fit-comparison engines for use with our scan data• Our back-end API server, and cloud deployment infrastructureI also collaborated on our mobile front-end, including development of client SDKs and custom data visualizations.

At Palantir, I adapted various mathematical, statistical, and machine learning techniques to solve business problems across a variety of industries, including oil & gas, healthcare, intelligence, law enforcement, television, and more.Selected projects include:• A personalized document feed used by intelligence analysts to surface urgent new reports• A viewership model used by a TV network to simulate and optimize promotional campaigns• A customer churn model used by a major payment processor to prioritize CRM efforts

I spent a summer at Schlumberger working as a data science intern.Some of my accomplishments from the summer include:• Developing algorithms to leverage autocorrelations in time-series data for predictive maintenance• Creating a time-series-oriented data visualization library for internal use• Configuring and documenting a Spark cluster for use by Schlumberger's various data analytics teams