The Future is Agentic in Recommender Systems
Kyle Polich sits down with Yashar Deldjoo, research scientist and Associate Professor at the Polytechnic University of Bari, to explore how recommender systems have evolved and why trustworthiness mat...
25 Apr 49min
Book Ratings and Recommendations
Goodreads star ratings can be misleading as measures of "book quality," and research from Hannes Rosenbusch suggests that for many professionally published books, differences between readers often mat...
27 Mar 39min
Disentanglement and Interpretability in Recommender Systems
Ervin Dervishaj, a PhD student at the University of Copenhagen, discusses his research on disentangled representation learning in recommender systems, finding that while disentanglement strongly corre...
10 Mar 30min
Collective Altruism in Recommender Systems
Ekaterina (Kat) Fedorova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively coordinate to game recommendation algorithms. Kat's research r...
27 Feb 54min
Niche vs Mainstream
Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose between mainstream and niche algorithms. His research shows spec...
18 Feb 34min
Healthy Friction in Job Recommender Systems
In this episode, host Kyle Polich speaks with Roan Schellingerhout, a fourth-year PhD student at Maastricht University, about explainable multi-stakeholder recommender systems for job recruitment. Roa...
2 Feb 26min
Fairness in PCA-Based Recommenders
In this episode, we explore the fascinating world of recommender systems and algorithmic fairness with David Liu, Assistant Research Professor at Cornell University's Center for Data Science for Enter...
26 Jan 49min
Video Recommendations in Industry
In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog "Silence Nogood." They explore the inter...
26 Des 202538min
