Professor Robin Burke conducts research in personalized recommender systems, a field he helped found and develop. His most recent projects explore fairness, accountability and transparency in recommendation through the integration of objectives from diverse stakeholders. Professor Burke is the author of more than 70 peer-reviewed articles in various areas of artificial intelligence including recommender systems, machine learning, and information retrieval. His work has received support from the National Science Foundation, the National Endowment for the Humanities, the Fulbright Commission, and the MacArthur Foundation, among others.
Recommender systems, Machine learning, Fairness and bias in recommender systems, Multistakeholder recommender systems, Digital humanities