The time allocated for each paper presentation will be 20 minutes (15 minutes for the presentation itself and 5 minutes for discussion).
Day 1 (7th, Wednesday)
| 11:30-13:00 | Lunch | |
| 13:00-13:10 | Opening | |
| 13:10-14:10 | Keynote 1: Katharina Morik | |
| 14:10-15:10 | Session 1: XAI I | |
| 14:10-14:30 | Mathieu Guilbert, Christel Vrain, Thi-Bich-Hanh Dao | A Constrained Declarative Based Approach for Explainable Clustering |
| 14:30-14:50 | Dongwhi Kim, Nuno Moniz | Relevance-aware Algorithmic Recourse |
| 14:50-15:10 | Genghua Dong, Henrik Bostrom, Michalis Vazirgiannis, Roman Bresson | Obtaining Example-Based Explanations from Deep Neural Networks |
| 15:10-15:30 | Break | |
| 15:30-17:30 | Session 2: Applications of Data Science I | |
| 15:30-15:50 | Bastien Mollet, Paul Ahavi, Antoine Cornuéjols, Jean-Loup Faulon, Evelyne Lutton, Alberto Tonda | Estimating the Learning Capacity of Bacterial Metabolic Networks |
| 15:50-16:10 | Ariel Basso Madjoukeng, Bélise Kenmogne Edith, Pierre Poitier, Benoît Frénay, Jérôme Fink | Local-global Data Augmentation for Contrastive Learning in Static Sign Language Recognition |
| 16:10-16:30 | Dorra Sassi, Constance Thierry, David Gross-Amblard | Credal Knowledge Tracing for Imprecise and Uncertain MCQ |
| 16:30-16:50 | Anne Rother, Till Ittermann, Myra Spiliopoulou | Semi-supervised learning with pairwise instance comparisons for medical instance classification |
| 16:50-17:10 | Daniel Persson, William Wahlberg, Anna Vettoruzzo, Slawomir Nowaczyk | Bridging Spatial and Temporal Contexts: Sparse Transfer Learning |
| 17:10-17:30 | Stijn Rotman, Gianluca Guglielmo, Boris Cule, Michal Klincewicz | Expertise Prediction of Tetris Players Using Eye Tracking Information |
| 17:30-18:30 | Aperitif on Terrace | |
| 18:30- | Rhine Terrace Dinner & Grill | |
Day 2 (8th, Thursday)
| 09:00-10:00 | Keynote II: Jessica Lin | |
| 10:00-11:00 | Session 3: XAI II | |
| 10:00-10:20 | Benoît Ronval, Pierre Dupont, Siegfried Nijssen | Detection of Large Language Model Contamination with Tabular Data |
| 10:20-10:40 | Rikard Vinge, Stefan Byttner, Jens Lundström | Expanding Polynomial Kernels for Global and Local Explanations of Support Vector Machines |
| 10:40-11:00 | Rik Adriaensen, Jaron Maene | Extracting Moore Machines from Transformers using Queries and Counterexamples |
| 11:00-11:30 | Break | |
| 11:30-12:10 | Session 4: Applications of Data Science II | |
| 11:30-11:50 | Bouke Scheltinga, Jasper Reenalda, Jaap Buurke, Joost Kok | Development of Models to Quantify Training Load in Outdoor Running using Inertial Sensors |
| 11:50-12:10 | Quentin Victor; Ianis Clavier, Hugo Boisaubert, Fabien Picarougne, Corinne Lejus-Bourdeau, Christine Sinoquet | Two-in-one Models for Event Prediction and Time Series Forecasting. Comparison of Four Deep Learning Approaches to Simulate a Digital Patient under Anesthesia |
| 12:10-12:30 | PhD Poster Spotlights | |
| 12:30-13:00 | PhD Mentorship | |
| 12:30-14:00 | Flying Lunch & Poster Session | |
| 14:00-15:40 | Session 5: Foundations of Data Science | |
| 14:00-14:20 | Loren Nuyts, Jesse Davis | The When and How of Target Variable Transformations |
| 14:20-14:40 | Sietse Schröder, Mitra Baratchi, Jan Van Rijn | Overfitting in Combined Algorithm Selection and Hyperparameter Optimization |
| 14:40-15:00 | Mateusz Żarski, Slawomir Nowaczyk | Balancing performance and scalability of demand forecasting ML models |
| 15:00-15:10 | Soroush Ghandi, Benjamin Quost, Cassio de Campos | Imposing Constraints in Probabilistic Circuits via Gradient Optimization |
| 15:10-15:40 | Lise Kastner, Cuissart Bertrand, Jean-Luc Lamotte | BOWSA: a contribution of sensitivity analysis to improve Bayesian optimization for parameter tuning |
| 15:40-16:10 | Break & Poster Session | |
| 16:10-17:30 | Session 6: Temporal Data Mining | |
| 16:10-16:30 | Nuwan Gunasekara, Slawomir Nowaczyk, Sepideh Pashami | Pragmatic Paradigm for Multi-stream Regression |
| 16:30-16:50 | Miro Miranda, Francisco Mena, Andreas Dengel | An Analysis of Temporal Dropout in Earth Observation Time Series for Regression Tasks |
| 16:50-17:10 | Ricardo Inácio, Vitor Cerqueira , Marília Barandas, Carlos Soares | Meta-learning and Data Augmentation for Stress Testing Forecasting Models |
| 17:10-17:30 | Julian Vexler, Björn Vieten, Martin Nelke, Stefan Kramer | Integrating Inverse and Forward Modeling for Sparse Temporal Data from Sensor Networks |
| 18:30-23:00 | Excursion to Mainau and Banquet Dinner | |
Day 3 (9th, Friday)
| 09:00-10:00 | Session 7: Representation Learning | ||
| 09:00-09:20 | Maciej Makowski, Brandon Gower-Winter, Georg Krempl | Performative Drift Resistant Classification using Generative Domain Adversarial Networks | |
| 09:20-09:40 | Maedeh Nasri, Mitra Baratchi, Alexander Koutamanis, Carolien Rieffe | SiamCircle: Trajectory Representation Learning in Free Settings | |
| 09:40-10:00 | Canberk Ozen, Slawomir Nowaczyk, Prayag Tiwari, Sepideh Pashami | Assessing the Impact of Graph Structure Learning in Graph Deviation Networks | |
| 10:00-11:00 | IDA from 1995 to today: A 30-Year Retrospective | ||
| 11:00-11:30 | Break | ||
| 11:30-12:50 | Session 8: Data Mining | ||
| 11:30-11:50 | Tsuyoshi Yamashita, Kunitake Kaneko | Balancing global importance and source proximity for personalized recommendations using random walk length | |
| 11:50-12:10 | G. Charbel N. Kindji, Elisa Fromont, Lina Maria Rojas-Barahona, Tanguy Urvoy | Synthetic Tabular Data Detection In the Wild | |
| 12:10-12:30 | Carl Vico Heinrich, Tommie Lombarts, Jules Mallens, Luc Tortike, David Wolf, Wouter Duivesteijn | Local Subgroup Discovery on Attributed Network Graphs | |
| 12:30-12:50 | Marco Loog, Jesse Krijthe, Manuele Bicego | Counterintuitive Behavior of Clustering Quality: Findings for K-Means on Synthetic and Real Data | |
| 12:50-14:00 | Lunch | ||
| 14:00-15:40 | Session 9: Natural Language Processing | ||
| 14:00-14:20 | Johannes Schneider | Improving Next Tokens via Second-to-Last Predictions with Generate and Refine | |
| 14:20-14:40 | Clémence Sebe, Sarah Cohen-Boulakia, Olivier Ferret, Aurélie Névéol | Extracting information in a low-resource setting: case study on bioinformatics workflows | |
| 14:40-15:00 | Vu Minh Hoang Dang, Rakesh Verma | Vocabulary Quality in NLP Datasets: An Autoencoder-Based Framework Across Domains and Languages | |
| 15:00-15:20 | Noor Khalal, Abdallah Djamai, Imed Keraghel, Mohamed Nadif | Imbalanced Data Clustering via Targeted Data Augmentation Using GMM and LLM | |
| 15:20-15:40 | Bojan Cestnik, Andrej Kastrin, Boshko Koloski, Nada Lavrač | Make Literature-Based Discovery Great Again through Reproducible Pipelines | |
| 15:40-16:00 | Closing Remarks | ||
| 16:00- | Farewell Drinks | ||