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PODCAST

Recsperts - Recommender Systems Experts

Marcel Kurovski

Recommender Systems are the most challenging, powerful and ubiquitous area of machine learning and artificial intelligence. This podcast hosts the experts in recommender systems research and application. From understanding what users really want to driving large-scale content discovery - from delivering personalized online experiences to catering to multi-stakeholder goals. Guests from industry and academia share how they tackle these and many more challenges. With Recsperts coming from universities

technology mathematics

All Episodes

97:25

#29: Transformers for Recommender Systems with Craig...

Recsperts - Recommender Systems Experts ·

2025/08/27

In episode 29 of Recsperts, I welcome Craig Macdonald, Professor of Information Retrieval at the University of Glasgow, and Aleksandr “Sasha” Petrov, PhD researcher and former applied scientist at Amazon. Together, we dive deep into sequential recommender systems and the growing role of transformer models such as SASRec and BERT4Rec.Our conversation begins with their influential replicability study of BERT4Rec, which revealed inconsistencies in reported results and highlighted the

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95:07

#28: Multistakeholder Recommender Systems with Robin...

Recsperts - Recommender Systems Experts ·

2025/04/15

In episode 28 of Recsperts, I sit down with Robin Burke, professor of information science at the University of Colorado Boulder and a leading expert with over 30 years of experience in recommender systems. Together, we explore multistakeholder recommender systems, fairness, transparency, and the role of recommender systems in the age of evolving generative AI.We begin by tracing the origins of recommender systems, traditionally built around user-centric models. However, Robin challenges

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87:44

#27: Recommender Systems at the BBC with Alessandro...

Recsperts - Recommender Systems Experts ·

2025/03/19

In episode 27 of Recsperts, we meet Alessandro Piscopo, Lead Data Scientist in Personalization and Search, and Duncan Walker, Principal Data Scientist in the iPlayer Recommendations Team, both from the BBC. We discuss how the BBC personalizes recommendations across different offerings like news or video and audio content recommendations. We learn about the core values for the oldest public service media organization and the collaboration with editors in that process.The BBC once started

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95:42

#26: Diversity in Recommender Systems with Sanne...

Recsperts - Recommender Systems Experts ·

2025/02/19

In episode 26 of Recsperts, I speak with Sanne Vrijenhoek, a PhD candidate at the University of Amsterdam’s Institute for Information Law and the AI, Media & Democracy Lab. Sanne’s research explores diversity in recommender systems, particularly in the news domain, and its connection to democratic values and goals.We dive into four of her papers, which focus on how diversity is conceptualized in news recommender systems. Sanne introduces us to five rank-aware divergence metrics for

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39:39

#25: RecSys 2024 Special

Recsperts - Recommender Systems Experts ·

2024/10/12

In episode 25, we talk about the upcoming ACM Conference on Recommender Systems 2024 (RecSys) and welcome a former guest to geek about the conference. Enjoy this enriching episode of RECSPERTS - Recommender Systems Experts.Don't forget to follow the podcast and please leave a review(00:00) - Introduction(01:56) - Overview RecSys 2024 (07:01) - Contribution Stats (09:37) - Interview Links from the Episode:RecSys 2024 Conference WebsitePapers:RecSys '24: Proceedings of the 18th ACM

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81:20

#24: Video Recommendations at Facebook with Amey...

Recsperts - Recommender Systems Experts ·

2024/10/01

In episode 24 of Recsperts, I sit down with Amey Dharwadker, Machine Learning Engineering Manager at Facebook, to dive into the complexities of large-scale video recommendations. Amey, who leads the Video Recommendations Quality Ranking team at Facebook, sheds light on the intricate challenges of delivering personalized video feeds at scale. Our conversation covers content understanding, user interaction data, real-time signals, exploration, and evaluation techniques.We kick off the episode

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114:58

#23: Generative Models for Recommender Systems with...

Recsperts - Recommender Systems Experts ·

2024/08/16

In episode 23 of Recsperts, we welcome Yashar Deldjoo, Assistant Professor at the Polytechnic University of Bari, Italy. Yashar's research on recommender systems includes multimodal approaches, multimedia recommender systems as well as trustworthiness and adversarial robustness, where he has published a lot of work. We discuss the evolution of generative models for recommender systems, modeling paradigms, scenarios as well as their evaluation, risks and harms.We begin our interview with a

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84:07

#22: Pinterest Homefeed and Ads Ranking with Prabhat...

Recsperts - Recommender Systems Experts ·

2024/06/06

In episode 22 of Recsperts, we welcome Prabhat Agarwal, Senior ML Engineer, and Aayush Mudgal, Staff ML Engineer, both from Pinterest, to the show. Prabhat works on recommendations and search systems at Pinterest, leading representation learning efforts. Aayush is responsible for ads ranking and privacy-aware conversion modeling. We discuss user and content modeling, short- vs. long-term objectives, evaluation as well as multi-task learning and touch on counterfactual evaluation as well.In

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95:46

#21: User-Centric Evaluation and Interactive...

Recsperts - Recommender Systems Experts ·

2024/04/08

In episode 21 of Recsperts, we welcome Martijn Willemsen, Associate Professor at the Jheronimus Academy of Data Science and Eindhoven University of Technology. Martijn's researches on interactive recommender systems which includes aspects of decision psychology and user-centric evaluation. We discuss how users gain control over recommendations, how to support their goals and needs as well as how the user-centric evaluation framework fits into all of this.In our interview, Martijn outlines

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