I currently work on Automated Machine Learning, building systems to outperform data scientists at training and productionizing ML solutions. My main expertise is in distributed systems, writing production-grade software, and large-scale machine learning. Before Microsoft, I was at Google where I worked on datacenter infrastructure, self-driving car technology, YouTube video transcoding, and Tensorflow. Before Google I led a research team at Sandia National Lab helping to design supercomputers for the DOE. My academic background is in computer architecture, silicon photonics, and simulation and modeling. I have a PhD from Columbia University and undergraduate degrees from the Rochester Institute of Technology.