Dr. Lee is a researcher with expertise in large scale machine learning and with experience working on projects in aviation, finance, internet, and automotive sectors. Previously he worked as a research scientist working on web search engine, fleet level prognostics, and revenue forecasting models. He serves as a reviewer for machine learning conferences and journals.

Dr. Lee’s research is inspired by geometric problems ubiquitous in natural science, web, and IoT applications. In natural science, simulation of celestial bodies can model galaxy formation and redshift. In web applications, web searches serve many consumers with text, image, and video content. IoT applications utilize predictive maintenance models to prevent catastrophic failures of potentially expensive industrial assets. Many of these applications at heart involve computational methods processing point sets in metric spaces. His research focuses on implementation and analysis of core methods powering industrial applications.

Learn more about Dr. Lee.