Recsperts - Recommender Systems Experts
21 episodes - English - Latest episode: 5 months ago - ★★★★★ - 1 ratingRecommender 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 all around the globe or from various industries like streaming, ecommerce, news, or social media, this podcast provides depth and insights. We go far beyond your 101 on RecSys and the shallowness of another matrix factorization based rating prediction blogpost! The motto is: be relevant or become irrelevant!
Expect a brand-new interview each month and follow Recsperts on your favorite podcast player.
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Episodes
#20: Practical Bandits and Travel Recommendations with Bram van den Akker
November 16, 2023 11:14 - 1 hour - 96.3 MBIn episode 20 of Recsperts, we welcome Bram van den Akker, Senior Machine Learning Scientist at Booking.com. Bram's work focuses on bandit algorithms and counterfactual learning. He was one of the creators of the Practical Bandits tutorial at the World Wide Web conference. We talk about the role of bandit feedback in decision making systems and in specific for recommendations in the travel industry. In our interview, Bram elaborates on bandit feedback and how it is used in practice...
#19: Popularity Bias in Recommender Systems with Himan Abdollahpouri
October 12, 2023 11:00 - 1 hour - 93.1 MBIn episode 19 of Recsperts, we welcome Himan Abdollahpouri who is an Applied Research Scientist for Personalization & Machine Learning at Spotify. We discuss the role of popularity bias in recommender systems which was the dissertation topic of Himan. We talk about multi-objective and multi-stakeholder recommender systems as well as the challenges of music and podcast streaming personalization at Spotify. In our interview, Himan walks us through popularity bias as the main cause o...
#18: Recommender Systems for Children and non-traditional Populations
August 17, 2023 15:50 - 1 hour - 91.2 MBIn episode 18 of Recsperts, we hear from Professor Sole Pera from Delft University of Technology. We discuss the use of recommender systems for non-traditional populations, with children in particular. Sole shares the specifics, surprises, and subtleties of her research on recommendations for children. In our interview, Sole and I discuss use cases and domains which need particular attention with respect to non-traditional populations. Sole outlines some of the major challenges lik...
#17: Microsoft Recommenders and LLM-based RecSys with Miguel Fierro
June 15, 2023 12:32 - 1 hour - 57.7 MBIn episode 17 of Recsperts, we meet Miguel Fierro who is a Principal Data Science Manager at Microsoft and holds a PhD in robotics. We talk about the Microsoft recommenders repository with over 15k stars on GitHub and discuss the impact of LLMs on RecSys. Miguel also shares his view of the T-shaped data scientist. In our interview, Miguel shares how he transitioned from robotics into personalization as well as how the Microsoft recommenders repository started. We learn more about t...
#16: Fairness in Recommender Systems with Michael D. Ekstrand
May 17, 2023 09:35 - 1 hour - 94.1 MBIn episode 16 of Recsperts, we hear from Michael D. Ekstrand, Associate Professor at Boise State University, about fairness in recommender systems. We discuss why fairness matters and provide an overview of the multidimensional fairness-aware RecSys landscape. Furthermore, we talk about tradeoffs, methods and receive practical advice on how to get started with tackling unfairness. In our discussion, Michael outlines the difference and similarity between fairness and bias. We discus...
#15: Podcast Recommendations in the ARD Audiothek with Mirza Klimenta
April 27, 2023 10:00 - 1 hour - 72.5 MBIn episode 15 of Recsperts, we delve into podcast recommendations with senior data scientist, Mirza Klimenta. Mirza discusses his work on the ARD Audiothek, a public broadcaster of audio-on-demand content, where he is part of pub. Public Value Technologies, a subsidiary of the two regional public broadcasters BR and SWR. We explore the use and potency of simple algorithms and ways to mitigate popularity bias in data and recommendations. We also cover collaborative filtering and var...
#14: User Modeling and Superlinked with Daniel Svonava
March 15, 2023 13:52 - 1 hour - 94.5 MBIn episode number 14 of Recsperts we talk to Daniel Svonava, CEO and Co-Founder of Superlinked, delivering user modeling infrastructure. In his former role he was a senior software engineer and tech lead at YouTube working on ad performance prediction and pricing. We discuss the crucial role of user modeling for recommendations and discovery. Daniel presents two examples from YouTube’s ad performance forecasting to demonstrate the bandwidth of use cases for user modeling. We also d...
#13: The Netflix Recommender System and Beyond with Justin Basilico
February 15, 2023 12:44 - 1 hour - 74.8 MBThis episode of Recsperts features Justin Basilico who is director of research and engineering at Netflix. Justin leads the team that is in charge of creating a personalized homepage. We learn more about the evolution of the Netflix recommender system from rating prediction to using deep learning, contextual multi-armed bandits and reinforcement learning to perform personalized page construction. Deep content understanding drives the creation of useful groupings of videos to be show...
#12: From User Intent to Multi-Stakeholder Recommenders and Creator Economy with Rishabh Mehrotra
January 18, 2023 11:14 - 2 hours - 116 MBIn this episode of Recsperts we talk to Rishabh Mehrotra, the Director of Machine Learning at ShareChat, about users and creators in multi-stakeholder recommender systems. We learn more about users intents and needs, which brings us to the important matter of user satisfaction (and dissatisfaction). To draw conclusions about user satisfaction we have to perceive real-time user interaction data conditioned on user intents. We learn that relevance does not imply satisfaction as well a...
#11: Personalized Advertising, Economic and Generative Recommenders with Flavian Vasile
December 15, 2022 13:57 - 1 hour - 66.5 MBIn this episode of Recsperts we talk to Flavian Vasile about the work of his team at Criteo AI Lab on personalized advertising. We learn about the different stakeholders like advertisers, publishers, and users and the role of recommender systems in this marketplace environment. We learn more about the pros and cons of click versus conversion optimization and transition to econ(omic) reco(mmendations), a new approach to model the effect of a recommendations system on the users' decis...
#10: Recommender Systems in Human Resources with David Graus
November 16, 2022 11:30 - 1 hour - 59.1 MBIn episode number ten of Recsperts I welcome David Graus who is the Data Science Chapter Lead at Randstad Groep Nederland, a global leader in providing Human Resource services. We talk about the role of recommender systems in the HR domain which includes vacancy recommendations for candidates, but also generating talent recommendations for recruiters at Randstad. We also learn which biases might have an influence when using recommenders for decision support in the recruiting process...
#9: RecPack and Modularized Personalization by Froomle with Lien Michiels and Robin Verachtert
September 15, 2022 16:41 - 1 hour - 81.1 MBIn episode number nine of Recsperts we talk with the creators of RecPack which is a new Python package for recommender systems. We discuss how Froomle provides modularized personalization for customers in the news and e-commerce sectors. I talk to Lien Michiels and Robin Verachtert who are both industrial PhD students at the University of Antwerp and who work for Froomle. We also hear about their research on filter bubbles as well as model drift along with their RecSys 2022 contribu...
#8: Music Recommender Systems, Fairness and Evaluation with Christine Bauer
August 15, 2022 07:46 - 1 hour - 66.1 MBIn episode number eight of Recsperts we discuss music recommender systems, the meaning of artist fairness and perspectives on recommender evaluation. I talk to Christine Bauer, who is an assistant professor at the University of Utrecht and co-organizer of the PERSPECTIVES workshop. Her research deals with context-aware recommender systems as well as the role of fairness in the music domain. Christine published work at many conferences like CHI, CHIIR, ICIS, and WWW. In this episode...
#7: Behavioral Testing with RecList for Recommenders with Jacopo Tagliabue
July 07, 2022 09:59 - 1 hour - 57.8 MBIn episode number seven, we meet Jacopo Tagliabue and discuss behavioral testing for recommender systems and experiences from ecommerce. Before Jacopo became the director of artificial intelligence at Coveo, he had founded tooso, which was later acquired by Coveo. Jacopo holds a PhD in cognitive intelligence and made many contributions to conferences like SIGIR, WWW, or RecSys. In addition, he serves as adjunct professor at NYU. In this episode we introduce behavioral testing for r...
#6: Purpose-Aware Privacy-Preserving Recommendations with Manel Slokom
May 25, 2022 10:00 - 1 hour - 90.8 MBIn episode number six, we welcome Manel Slokom to the show and talk about purpose-aware privacy-preserving data for recommender systems. Manel is a 4th year PhD student at Delft University of Technology. For three years in a row she served as student volunteer at RecSys - before becoming student volunteer co-chair herself in 2021. Besides working on privacy and fairness, she also dedicates herself to simulation and in particular synthetic data for recommender systems - also co-organ...
#5: Fashion Recommendations with Zeno Gantner
May 03, 2022 13:32 - 1 hour - 78.1 MBIn episode five my guest is Zeno Gantner, who is a principal applied scientist at Zalando. Zeno obtained his PhD from the University of Hildesheim where he was investigating ML-based recommender systems. As a principal applied scientist he is responsible for strategy, mentoring and setting standards for different initiatives on fashion recommendations impacting over 48 million customers in Europe. We discuss the ramifications and limitations of positive-only implicit feedback, touc...
#4: Adversarial Machine Learning for Recommenders with Felice Merra
February 23, 2022 16:56 - 1 hour - 63.8 MBIn episode four my guest is Felice Merra, who is an applied scientist at Amazon. Felice obtained his PhD from Politecnico di Bari where he was a researcher at the Information Systems Lab (SisInf Lab). There, he worked on Security and Adversarial Machine Learning in Recommender Systems. We talk about different ways to perturb interaction or content data, but also model parameters, and elaborated various defense strategies. In addition, we touch on the motivation of individuals or wh...
#3: Bandits and Simulators for Recommenders with Olivier Jeunen
January 03, 2022 17:00 - 1 hour - 67.1 MBIn episode three I am joined by Olivier Jeunen, who is a postdoctoral scientist at Amazon. Olivier obtained his PhD from University of Antwerp with his work "Offline Approaches to Recommendation with Online Success". His work concentrates on Bandits, Reinforcement Learning and Causal Inference for Recommender Systems. We talk about methods for evaluating online performance of recommender systems in an offline fashion and based on rich logging data. These methods stem from fields li...
#2: Deep Learning based Recommender Systems with Even Oldridge
October 31, 2021 15:55 - 50 minutes - 45.9 MBIn episode two I am joined by Even Oldridge, Senior Manager at NVIDIA, who is leading the Merlin Team. These people are working on an open-source framework for building large-scale deep learning recommender systems and have already won numerous RecSys competitions. We talk about the relevance and impact of deep learning applied to recommender systems as well as the challenges and pitfalls of deep learning based recommender systems. We briefly touch on Even's early data science cont...
#1: Practical Recommender Systems with Kim Falk
October 08, 2021 12:02 - 1 hour - 73 MBIn this first interview we talk to Kim Falk, Senior Data Scientist, multiple RecSys Industry Chair and author of the book "Practical Recommender Systems". We introduce into recommenders from a practical perspective discussing the fundamental difference between content-based and collaborative filtering as well as the cold-start problem - no mathematical deep-dive yet, but expect it to follow. In addition, we reason what constitutes good recommendations and briefly touch on a couple o...
#0: Launching Recsperts - the Recommender Systems Experts Podcast
September 23, 2021 13:06 - 13 minutes - 11.1 MBHave you ever though about how Spotify is able to generate its fantastic Discover Weekly Playlist, how Amazon is generating a fortune by showing what other like you purchased in the past, or how Netflix achieves high user retention? The answer is personalization and in this show we focus on the most prominent way to achieve personalization: recommender systems. Whether you are a beginner and new to the field or you have already build recommenders, this show is to bring you the exper...