Daniel is a Data Scientist at Silicon Valley Data Science. Daniel’s Ph.D. research involved measuring the structure at the largest scales in the universe and tracing their evolution from the earliest moments up until to today. In order to accomplish this, he used observations from a multi-year telescope survey to construct the largest three-dimensional map of our universe to date. His work enables tests of Einstein’s theory of general relativity and helps physicists better understand the fundamental constituents of the universe, including the enigmatic dark energy, which drives our ever-expanding universe. In particular, he focused on developing and scaling algorithms for extracting signals from ever increasing volumes of data. Prior to joining SVDS, Daniel was a fellow at Insight Data Science. While at Insight, he developed a meal ingredient recommendation application that utilized a graph based analysis of ingredient flavor compounds and ingredient lists from publicly available recipe databases. Daniel graduated with a bachelor of science degree in physics from UCLA. He received his masters in physics from UC Irvine and will complete his Ph.D. in Physics there this year.