Staff Software Engineer / Engineering Manager

Worked on the open source project Apache Spark.

Made contributions to the Machine Learning Library (MLlib) for Spark.

Wrote performance tests for MLlib to monitor performance regressions and optimize when necessary.

Fully funded RA-ship. Developed a new method called Sampled Stochastic Subgradient (SaSS), that

combines two optimization frameworks: Randomized Linear Algebra (RLA) and Stochastic Gradient

Descent (SGD), as a best-of-both-worlds algorithm. The algorithm shows state-of-the-art performance

in the medium precision regime.