Papers must be written in English and formatted according to the Springer Lecture Notes in Computer Science (LNCS) guidelines, using the same format as the main conference.

The maximum length for both research papers and position papers is 16 pages, including references. Overlength papers will be rejected without review. Papers with smaller margins or font sizes than those specified in the author instructions and style files will also be treated as overlength.

We also accept full papers and 2 to 4 page abstracts, including references, for presentation only. These submissions may outline new emerging ideas and/or already published work, with the aim of stimulating discussion and collaboration among participants.

Authors who submit their work to XKDD 2026 commit to presenting their paper at the workshop if it is accepted. XKDD 2026 considers the author list submitted with the paper to be final. No additions or deletions may be made after submission, either during the review period or, in case of acceptance, at the final camera-ready stage.

When submitting a paper, authors should indicate in a note whether they wish to opt out of publication in the post-proceedings if the paper is accepted. All accepted full papers whose authors do not opt out will be published in the post-proceedings as part of the Lecture Notes in Computer Science series.

A condition for inclusion in the post-proceedings is that at least one co-author presents the paper at the workshop. Pre-proceedings will be made available online before the workshop.

All deadlines expire on 23:59 AoE.

• Paper Submission deadline: June 5th, 2026 June 12th, 2026
• Accept/Reject Notification: July 5th, 2026 July 8th, 2026
• Camera-ready deadline: September 20th, 2026
• Workshop: September 7th, 2026 (Full Day)

Program Chairs

Francesca Naretto

KDD Lab, University of Pisa, Italy

Francesco Spinnato

KDD Lab, University of Pisa, Italy

Przemyslaw Biecek

Warsaw University of Technology, Warsaw, Poland

Andreas Theissler

Institut für Informatik, Justus Liebig University Giessen, Germany

Invited Speakers

Peter Flach

Professor of Artificial Intelligence, School of Computer Science, University of Bristol

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Peter Flach holds an M.Sc. from Twente and a Ph.D. from Tilburg. He has been Professor of Artificial Intelligence at the University of Bristol since 2003. He is an internationally leading researcher in mining highly structured data and in the evaluation and improvement of machine learning models using ROC analysis. He has also published on the logic and philosophy of machine learning, and on the combination of logic and probability. He is the author of Simply Logical: Intelligent Reasoning by Example (John Wiley, 1994) and Machine Learning: the Art and Science of Algorithms that Make Sense of Data (Cambridge University Press, 2012). From 2010 to 2020, Prof Flach was Editor-in-Chief of the Machine Learning journal. He was Programme Co-Chair of ILP 1999, ECML 2001, KDD 2009, and ECML PKDD 2012 in Bristol. He is a founding board member, former President, and current Vice-President of the European Association for Data Science. His research has been funded by UKRI, EPSRC, MRC, TSB, and the EU, among others. He is currently Director of the UKRI Centres for Doctoral Training in Interactive Artificial Intelligence and Practice-Oriented Artificial Intelligence. His main expertise is in machine learning, data science, human-centred artificial intelligence, and practice-oriented artificial intelligence.

Georgiana Ifrim

Associate Professor, School of Computer Science, University College Dublin

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Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, University College Dublin, Director of the Research Ireland Centre for Research Training in Machine Learning (ML-Labs), and a Funded Investigator with the Insight Centre for Data Analytics. She previously served as Director of Graduate Research at UCD Computer Science, receiving the GEM School Award twice, and was nominated in 2023 for the UCD Graduate Studies Dean’s Award for Excellence in Doctoral Supervision. She holds a PhD and MSc in Computer Science from the Max Planck Institute for Informatics, Germany, and a BSc from the University of Bucharest. Her research focuses on scalable machine learning, data mining, interpretable models for sequential data, including time series, and text mining. She has published over 50 peer-reviewed papers in leading venues such as KDD, ACL, WWW, ICDE, ECML, COLING, TKDE, and DMKD. Dr. Ifrim is a senior editorial board member of the Machine Learning Journal and regularly serves in senior roles for major conferences including AAAI, IJCAI, and ECML-PKDD. Her team develops open-source software and industry research prototypes, and has won three international data modelling competitions: SNOW 2014, Spectroscopy 2022, and Spectroscopy 2024.

Program Committee

• Alessio Cascione, University of Pisa
• Andrea Pugnana, University of Trento
• Andreas Theissler, Justus Liebig University Giessen
• Benedetta Muscato, Scuola Normale Superiore
• Cristiano Landi, University of Pisa
• Dawid Płudowski, Centre of Credible AI, Warsaw University of Technology
• Eleonora Cappuccio, University of Pisa
• Felix Gerschner, Justus Liebig University Giessen
• Francesca Naretto, University of Pisa
• Francesco Spinnato, University of Pisa
• Giacomo Fidone, University of Pisa
• Gizem Gezici, Scuola Normale Superiore
• Hubert Baniecki, University of Warsaw
• Lorenzo Mannocci, University of Pisa
• Luca Corbucci, Bruno Kessler Foundation
• Mario Refoyo, Universidad Politécnica de Madrid
• Marta Marchiori Manerba, University of Turin
• Martina Cinquini, University of Pisa
• Martino Ciaperoni, Scuola Normale Superiore
• Mattia Setzu, University of Pisa
• Miquel Miró Nicolau, Universitat de les Illes Balears (UIB)
• Przemyslaw Biecek, Warsaw University of Technology
• Simone Piaggesi, University of Pisa
• Udo Schlegel, LMU Munich
• Valerio Bonsignori, Scuola Normale Superiore