lien$ whoami
Interdisciplinary researcher who is genuinely passionate about fostering diverse exposure and discovery through algorithmic recommendation. Creative problem solver and team player, with a love for cross-disciplinary collaboration.
Featured Projects
In every job that must be done, there is an element of fun. You find the fun and - SNAP - the job's a game! Here are some of my favorite jobsgames of the last years
RecPack
AGPL 3.0RecPack is an experimentation toolkit for top-N recommendation using implicit feedback data. Its goals is to support researchers who advance the state-of-the-art in top-N recommendation to write reproducible and reusable experiments.
Measuring Filter Bubbles in Online News
MITGeneralized Linear Mixed-Effects Model (GLMM) to measure filter bubbles on an online news website. Includes code to preprocess data and run model.
RecPack Tests
PublishedRecPack Tests is a testing toolkit for top-N recommendation algorithms.
Publications
Mitigating Misleadingness in LLM-Generated Natural Language Explanations for Recommender Systems: Ensuring Broad Truthfulness Through Factuality and Faithfulness
Authors: Maes, Ulysse; Michiels, Lien; Smets, Annelien
Published in: In Press
What Is Serendipity? An Interview Study to Conceptualize Experienced Serendipity in Recommender Systems
Authors: Binst, Brett; Michiels, Lien; Smets, Annelien
Published in: Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization
Conversational Agents: A Framework for Evaluation (CAFE): Manifesto from Dagstuhl Perspectives Workshop 24352
Authors: Bauer, Christine; Chen, Li; Ferro, Nicola; Fuhr, Norbert; Avishek, Anand; Breuer, Timo; Faggioli, Guglielmo; Frieder, Ophir; Joho, Hideo; Karlgren, Jussi; et al.
Published in: Dagstuhl Manifestos
Methodologies to Evaluate Recommender Systems
Authors: Michiels, Lien
Published in: University of Antwerp
A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms
Authors: Michiels, Lien; Verachtert, Robin; Ferraro, Andres; Falk, Kim; Goethals, Bart
Published in: ACM Transactions on Recommender Systems
GenUI (ne) CRS: UI Elements and Retrieval-Augmented Generation in Conversational Recommender Systems with LLMs
Authors: Maes, Ulysse; Michiels, Lien; Smets, Annelien
Published in: Proceedings of the 18th ACM Conference on Recommender Systems
NORMalize 2024: The Second Workshop on Normative Design and Evaluation of Recommender Systems
Authors: Starke, Alain; Vrijenhoek, Sanne; Michiels, Lien; Kruse, Johannes; Tintarev, Nava
Published in: Proceedings of the 18th ACM Conference on Recommender Systems
Informed Dataset Selection with 'Algorithm Performance Spaces'
Authors: Beel, Joeran; Wegmeth, Lukas; Michiels, Lien; Schulz, Steffen
Published in: Proceedings of the 18th ACM Conference on Recommender Systems
Theory of Evaluation: Evaluation Perspectives of Recommender Systems: Driving Research and Education (Dagstuhl Seminar 24211)
Authors: Hurley, Neil; Anelli, Vito Walter; Bellogín, Alejandro; Jeunen, Olivier; Michiels, Lien; Parra, Denis; Santos, Rodrygo LT; Tuzhilin, Alexander
Published in: Dagstuhl Reports, Volume 14, Issue 5
NORMalize: A Tutorial on the Normative Design and Evaluation of Information Access Systems
Authors: Kruse, Johannes; Michiels, Lien; Starke, Alain; Tintarev, Nava; Vrijenhoek, Sanne
Published in: Proceedings of the 2024 ACM SIGIR Conference on Human Information Interaction and Retrieval
How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News
Authors: Michiels, Lien; Vannieuwenhuyze, Jorre; Leysen, Jens; Verachtert, Robin; Smets, Annelien; Goethals, Bart
Published in: Proceedings of the 17th ACM Conference on Recommender Systems
NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems
Authors: Vrijenhoek, Sanne; Michiels, Lien; Kruse, Johannes; Starke, Alain; Tintarev, Nava; Viader Guerrero, Jordi
Published in: Proceedings of the 17th ACM Conference on Recommender Systems
The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance
Authors: Verachtert, Robin; Craps, Jeroen; Michiels, Lien; Goethals, Bart
Published in: Advances in Information Retrieval: 45th European Conference on Information Retrieval, ECIR 2023
Reality Check–Conducting Real World Studies (Dagstuhl Seminar 23031)
Authors: Ferwerda, Bruce; Hanbury, Allan; Knijnenburg, Bart P; Larsen, Birger; Michiels, Lien; Papenmeier, Andrea; Said, Alan; Schaer, Philipp; Willemsen, Martijn
Published in: Dagstuhl Reports, Volume 13, Issue 1
What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work
Authors: Michiels, Lien; Leysen, Jens; Smets, Annelien; Goethals, Bart
Published in: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
RecPack: An (other) Experimentation Toolkit for Top-N Recommendation Using Implicit Feedback Data
Authors: Michiels, Lien; Verachtert, Robin; Goethals, Bart
Published in: Proceedings of the 16th ACM Conference on Recommender Systems
Serendipity in Recommender Systems Beyond the Algorithm: A Feature Repository and Experimental Design
Authors: Smets, Annelien; Michiels, Lien; Bogers, Toine; Björneborn, Lennart
Published in: 16th ACM Conference on Recommender Systems
An Interpretable Model for Collaborative Filtering Using an Extended Latent Dirichlet Allocation Approach
Authors: Wilhelm, Florian; Mohr, Marisa; Michiels, Lien
Published in: The International FLAIRS Conference Proceedings
Are We Forgetting Something? Correctly Evaluate a Recommender System With an Optimal Training Window
Authors: Verachtert, Robin; Michiels, Lien; Goethals, Bart
Published in: Perspectives on the Evaluation of Recommender Systems Workshop (PERSPECTIVES) at RecSys22
Events & Speaking
Sharing knowledge and insights on filter bubbles, serendipity and evaluation methodologies at conferences, workshops, and summer schools
ACM RecSys 2025
NORMalize sets out to provide a platform for researchers and practicioners from different domains to discuss challenges related to the normative design and evaluation of recommender systems.
Presented my research on the what, why and how of measuring filter bubbles.
ACM RecSys 2024
NORMalize sets out to provide a platform for researchers and practicioners from different domains to discuss challenges related to the normative design and evaluation of recommender systems.
Dagstuhl Perspectives Workshop 24352
Contributed to the CAFE Manifesto for evaluating CONIAC systems.
Dagstuhl Seminar 24211
Contributed to working group 'Theory of Evaluation'.
ACM CHIIR 2024
Organized an on-site interactive tutorial for the norm-curious to promote normative thinking in the design of recommender/information retrieval systems.
ACM RecSys 2023
NORMalize sets out to provide a platform for researchers and practicioners from different domains to discuss challenges related to the normative design and evaluation of recommender systems.
Dagstuhl Seminar 23031
Contributed to working group 'Reality Check – Conducting Real World Studies'.
Teaching & Education
Fostering the next generation of ML researchers and practitioners
Courses
Python for Machine Learning
MSc.Faculty of Business & Economics, University of Antwerp
Comprehensive course covering Python programming, as well as topics in machine learning with a focus on classification.
Machine Learning for Business
MSc.Faculty of Business & Economics, University of Antwerp
Comprehensive course covering topics in machine learning including classification, clustering, pattern mining, natural language processing and neural network architectures.
Artificial Intelligence Project
MSc.Faculty of Science, Dept. of Informatics, University of Antwerp
Project-based course where students develop and executive a research plan for a data science task in a Kaggle-style competition format.
Guest Lectures
Introduction to Recommender Systems
Postgraduate Big Data
KULeuven • Industry, Postgraduate
Practical Considerations in Recommender Systems
Recommender Systems
Maastricht University • 3rd Year BSc. in Computer Science
News Recommender Systems
AI & Society
Vrije Universiteit Amsterdam • 2nd Year BSc. in Computational Social Science
Introduction to Recommender Systems
AI Applications
Thomas More Hogeschool • 3rd Year Professional Bachelors in Informatics
Awards & Honors
Recognition for my contributions to research and academic excellence
Best Reviewer Award
ACM UMAP
Recognized for my contributions as a program committee member. Joint effort with Hanne Vandenbroucke, Brett Binst and Ulysse Maes.
Distinguished Reviewer
ACM Transactions on Recommender Systems (TORS)
Recognized for my contributions as a reviewer for TORS.
Outstanding Reviewer Award
ACM RecSys
Recognized for my contributions as a program committee member.
Outstanding Reviewer Award
ACM UMAP
Recognized for my contributions as a program committee member.
Outstanding Reviewer Award
ACM RecSys
Recognized for my contributions as a program committee member.
Women in RecSys Journal Paper of the Year Award (Silver)
Women's Events at ACM RecSys
Awarded for my journal paper 'A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms', published in TORS.
Best Demo Award
ACM RecSys
Awarded for our demo 'RecPack: An (other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data'
Best Paper Award
PERSPECTIVES Workshop
Awarded for our workshop paper 'Are We Forgetting Something? Correctly Evaluate a Recommender System With an Optimal Training Window'