Recsperts - Recommender Systems Experts
Recsperts - Recommender Systems Experts
Marcel Kurovski
This podcast interviews experts in recommender systems from industry and academia. We talk about their background as well as how and why they joined this field. We discuss the basics, challenges as well as current approaches and technologies in personalizing online content for users. The show includes people from all sorts of technology sectors, like music or video streaming, e-commerce, news, or social media, but also researchers from universities around the globe that dedicate themselves to recommender systems research. In each episode we have a different guest and go into depth about certain subtopics as well as the particular approaches and achievements of our guest. Expect a bi-weekly episode on this show.
#6: Purpose-Aware Privacy-Preserving Recommendations with Manel Slokom
Episode number six of Recsperts is about purpose-aware privacy-preserving data for recommender systems. My guest is Manel Slokom, who is a 4th year PhD student at Delft University of Technology. She served as student volunteer at RecSys for three years in a row before becoming student volunteer co-chair herself in 2021. In addition to her work on privacy and fairness, she also dedicates herself to simulation and in particular synthetic data for recommender systems - also co-organizing the 1st SimuRec Workshop as part of RecSys 2021.
May 25, 2022
1 hr 39 min
#5: Fashion Recommendations with Zeno Gantner
Episode number five of Recsperts revolves around fashion recommendations in general and at Zalando in specific. My guest is Zeno Gantner, who is a principal applied scientist and works in one of several personalization teams at Zalando. As an individual contributor and part of the leadership team he drives personalization not only to recommend relevant clothing, but also to facilitate inspiration and discovery for Zalando’s customers. With a background in computer science and symbolic AI, Zeno spent his PhD on ML applied to recommender systems and contributed to various open source projects as well as served at RecSys as member of the senior program committee.
May 3, 2022
1 hr 24 min
#4: Adversarial Machine Learning for Recommenders with Felice Merra
In 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). He investigated Security and Adversarial Machine Learning in Recommender Systems by looking at different ways to perturb interaction or content data, but also model parameters, and elaborated various defense strategies.
Feb 23, 2022
1 hr 9 min
#3: Bandits and Simulators for Recommenders with Olivier Jeunen
In 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.
Jan 3, 2022
1 hr 12 min
#2: Deep Learning based Recommender Systems with Even Oldridge
In 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.
Oct 31, 2021
50 min
#1: Practical Recommender Systems with Kim Falk
In this first interview we talk to Kim Falk, Senior Data Scientist, multiple RecSys Industry Chair and author of the book "Practical Recommender Systems"
Oct 8, 2021
1 hr 19 min
#0: Launching Recsperts - the Recommender Systems Experts Podcast
In this first episode of Recsperts - Recommender Systems Experts I will introduce this new podcast show where we will have lots of interviews with experts in the field of recommender systems. From academia to industry, from application to theory - this podcast will cover all the topics in recommender systems.
Sep 23, 2021
13 min