Robert loves to break deep technical concepts down to be as simple as possible, but no simpler.
Robert has data science experience in companies both large and small. At Intel, he used his knowledge to tackle problems in data center optimization using cluster analysis, enriched market sizing models by implementing sentiment analysis from social media feeds, and improved data-driven decision making in one of the top 5 global supply chains. At Tamr, he built models to unify large amounts of messy data across multiple silos for some of the largest corporations in the world. He earned a PhD in Applied Mathematics from Arizona State University where his research spanned image reconstruction, dynamical systems, mathematical epidemiology and oncology. Robert is an Adjunct Professor at Santa Clara University’s Leavey School of Business and a Senior Data Scientist at Metis where he teaches Data Science and Machine Learning. In his spare time, he is a rum judge, avid traveler, and eater of all things coconut.