Tom is a statistician and data scientist at GV. Along with his quantitative skills, he brings expertise in big data analysis with web-scale data.
Prior to joining GV, Tom worked at Google for over nine years. He spent the first six years in Ads Quality, analyzing and modeling various aspects of Google’s advertising business, including ads quality evaluation and prediction, user experience, and experiment framework. He spent the next three years working with Hal Varian on the Economics team, conducting research on a wide range of data problems.
Tom received his Bachelor of Science in mathematics from Peking University, China and his Ph.D. in statistics from Stanford University. While in school, he interned at Xerox PARC and Sun Labs doing research on document image decoding and experimental design in high-dimensional space.