Intro to Recommender Systems: Non-Personalized & Content

Dr. Joseph A. Konstan is a distinguished professor in the Department of Computer Science and Engineering at the University of Minnesota, where he holds the title of Distinguished McKnight University Professor and Distinguished University Teaching Professor. His extensive research focuses on human-computer interaction, particularly in the areas of recommender systems, social computing, and public health applications. Notably, his work on the GroupLens Recommender System earned him the prestigious ACM Software Systems Award in 2010.Dr. Konstan received his A.B. from Harvard University and both his M.S. and Ph.D. from the University of California, Berkeley. He is recognized for his contributions to education through various teaching awards and has delivered numerous webinars and short courses on topics such as recommender systems and ethical issues in social computing. As a Fellow of the ACM, IEEE, and AAAS, he has also served as President of ACM SIGCHI and has chaired several major conferences in the field. His courses on Coursera include "Introduction to Recommender Systems," "Evaluating User Interfaces," and "User Research and Design," aimed at equipping students with essential skills in user experience and system design.

Dr. Michael D. Ekstrand is an Assistant Professor in the Department of Computer Science at Boise State University, where he focuses on evaluating and understanding recommender systems in relation to user goals and information needs. His research emphasizes supporting reproducible research in the field of recommender systems. Dr. Ekstrand is also the lead developer of LensKit, an open-source toolkit designed for building, researching, and studying recommender systems.He teaches several courses on Coursera, including "Introduction to Recommender Systems: Non-Personalized and Content-Based," "Matrix Factorization and Advanced Techniques," and "Recommender Systems Capstone." His work aims to enhance the effectiveness of recommendation algorithms while ensuring they meet user needs.Dr. Ekstrand earned his Ph.D. from the University of Minnesota and has contributed significantly to the field through his research and development efforts. He is actively involved in various academic initiatives and has presented at numerous conferences related to information science and recommender systems.