Carl Kadie, PhD

Carl M. Kadie is a retired principal applied researcher at Microsoft Research who spent his career developing machine learning methods for learning from data, most notably in collaborative filtering and recommendation systems. Kadie earned both his undergraduate and doctoral degrees at the University of Illinois at Urbana-Champaign, completing his doctorate in computer science with a dissertation on maximum likelihood regression for learning-speed curves — a statistical approach to modeling how quickly learners improve with practice. At Microsoft Research, he contributed to foundational work on collaborative filtering, the algorithmic backbone of modern recommendation systems used across the internet. He retired from Microsoft Research as a principal applied researcher.