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Siddhartha Sen is a Researcher at Microsoft Research in New York City, and previously a researcher at the MSR Silicon Valley lab. He designs and builds distributed systems that use novel data structures and algorithms to deliver new functionality or unprecedented performance. Some of his data structures have been incorporated into undergraduate textbooks and curricula. Recently, he has generalized this approach by using contextual machine learning to optimize decisions in a variety of settings, including Microsoft’s cloud infrastructure (check out our Decision Service).
Siddhartha received his BS degrees in computer science and mathematics and his MEng degree in Computer Science from MIT. From 2004-2007 he worked as a developer at Microsoft and built a network load balancer for Windows Server, holding several patents for this work. He returned to academia and received his PhD from Princeton University in 2013, spending his final year as a junior research scientist at New York University. Siddhartha received the first Google Fellowship in Fault-Tolerant Computing in 2009, the best student paper award at PODC 2012, and the best paper award at ASPLOS 2017.