About

Fan Yang, Ph.D. is a seasoned data scientist and machine learning engineer with 5 years of experience in computational advertising across publisher, DSP, ad exchange, and ad network. He is skilled in machine learning, optimization, and mathematical modeling. Fan has a strong engineering background with a Doctor of Philosophy (Ph.D.) in Geophysics from Stanford University and is the first author of a Nature paper in 2018. Currently, Fan is a Senior Machine Learning Engineer at tapjoy, a mobile gaming ad network, where he is responsible for WinRate modeling, budget pacing, and ads ranking. Prior to tapjoy, Fan worked as a Senior Machine Learning Engineer at groundtruth, a location-based advertising DSP, where he focused on ads inventory forecasting and optimal real-time bidding (RTB) for display advertising using convex optimization and MAB. He also worked as a Machine Learning Engineer at Disney Ad Network, where he developed the UP//LIFT model on publisher side ads serving optimization and ads delivery pacing using PID control. Fan's educational background includes a Ph.D. in Geophysics from Stanford University and a Bachelor's degree in Geophysics from the University of Science and Technology of China. His technical skills include ML, data scientist, research scientist, and mobile. Fan has 5.94 years of relevant experience in the field of computational advertising and machine learning engineering.