Ekstrand, Michael

Michael Ekstrand is an assistant professor in the Department of Computer Science at Boise State University, where he co-directs the People and Information Research Team (PIReT, pronounced ‘pirate’). He studies human-computer interaction and artificial intelligence, working to ensure information access systems — particularly recommender systems — are good for the people they affect. He received his Ph.D. in 2014 from the University of Minnesota, building tools reproducible research and examining user-relevant differences in recommender algorithms with the GroupLens research group; leads the LensKit open-source software project for enabling high-velocity reproducible research in recommender systems; co-created the Recommender Systems specialization on Coursera with Joseph A. Konstan from the University of Minnesota; and is involved with organizing several workshops and events on fairness and responsibility in recommender systems and information retrieval, including FAccTRec, FACTS-IR, and the Fairness track at TREC. In 2018, he received the NSF CAREER award to fund his study of recommender system response to biases in input data and experimental protocols and their projected impact under various technical and sociological conditions.

https://md.ekstrandom.net/
https://twitter.com/mdekstrand