Teaching, Talks, and Outreach

Teaching

  • Teaching assistant for the Data Preparation for Machine Learning course for master’s students at the University of Amsterdam and Vrije Universiteit Amsterdam (2024).
  • Teaching assistant for the Big Data course for master’s students at the University of Amsterdam (2022).

Guest lectures and talks

  • Guest lecture for the Econometrics master’s students at the University of Amsterdam on often-bought-together product recommendations (2024). Course page
  • Guest lecture for the AI and Data Science master’s students in the Big Data course at the University of Amsterdam on category-prediction recommendations (2024).
  • Guest lecture for the Econometrics master’s students at the University of Amsterdam on self-supervised contrastive learning for product recommendations (2023). Course page
  • Guest lecture at Tilburg University on session-based recommendations, their use in industry, and our work on the topic (2022). Tilburg University
  • Guest lecture for the Econometrics master’s students at the University of Amsterdam on category-prediction recommendations (2022). Course page
  • Guest lecture on bol.com’s “verder kijken” recommendations for bachelor’s students in the Data Mining class (2022). University of Technology Delft
  • Guest lecture at Tilburg University on retail recommendations for master’s students in Customer Analytics (2021). Tilburg University

Research and industry outreach

  • Presented at RecSys 2025 on the KMC-Shapley algorithm for calculating Data Shapley values and optimizing sequential k-nearest-neighbor recommendation systems. Illoominate on GitHub
  • Presented our work on ETUDE - Evaluating the Inference Latency of Session-Based Recommendation Models at Scale at the IEEE International Conference on Data Engineering (ICDE 2024). ICDE 2024
  • Presented Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale at SIGMOD 2022. SIGMOD
  • Presented work on scalable session-based recommendation at the ECIR 2022 industry day. ECIR
  • Presented work on low-latency recommendations at the DBDBD 2021 workshop. DBDBD
  • Ran a recommender-systems workshop for data scientists at Albert Heijn, including a live demonstration of Serenade (2022).
  • Presented studies on improving the predictive performance of bol.com’s recommender system at the Cologne AI and Machine Learning meetup (2021). Meetup
  • Joined the bol.com Techlab podcast to discuss the AI for Retail Lab and recommender systems (2021). Podcast
  • Participated in the ICAI Day poster session on AI and climate change (2022). ICAI Day
  • Open-sourced Serenade, a Rust-based k-nearest-neighbor recommender system powering product recommendations at bol.com (2022). Serenade on GitHub