Overview

Key Dates

Call for Papers

Following the success of the first two editions, the HLDM 2025 workshop aims at gathering together a diverse set of researchers addressing the different aspects that characterise effective hybrid decision making. These range from machine learning approaches that explicitly account for the human-in-the-loop and the downstream goal of the human-machine system, to decision making strategies and HCI principles encouraging a rich and diverse interaction between the human and the machine, to cognitive aspects pinpointing potential pitfalls, misunderstandings and sub-optimal behaviour, legal and regulatory aspects highlighting requirements and constraints that trustworthy and ethical hybrid decision making systems should satisfy. The workshop will feature invited talks, a poster session, presentations of the best contributions and a final discussion.

We invite submissions on a broad range of topics revolving around hybrid human-machine learning and decision making, including but not limited to:

• learning to defer

• learning to complement

• selective classification

• cost-sensitive learning

• active learning

• calibration of learning models

• interactive machine learning

• human-in-the-loop machine learning

• trustworthy hybrid decision making

• human-LLM decision making

• cognitive aspects in hybrid decision making

• theoretical models of hybrid decision making

• hybrid decision-making interfaces

• hybrid decision-making strategies

• hybrid decision-making applications

• hybrid decision making in multiparty settings

• human factors and decision making

• regulation of hybrid decision-making systems

• assessment of hybrid decision-making systems

• ethics of hybrid decision-making

• legal aspects of decision support systems

The goal of the workshop is to foster discussion on the most promising research directions and the most relevant challenges revolving around hybrid human-machine learning and decision making. We thus accept the following types of submissions:

1. Short papers (6 pages + references) presenting work-in-progress, position papers or open problems with clear and concise formulations of current challenges. Short papers should be anonymized (double-blind review process) and formatted according to the ECMLPKDD 2025 guidelines (see here). Accepted short papers will be included in the Springer Workshop proceedings of ECMLPKDD 2025.

2. Regular papers (14 pages + references) presenting novel original work not published elsewhere. Regular papers should be anonymized (double-blind review process) and formatted according to the ECMLPKDD 2025 guidelines (see here). Accepted regular papers will be included in the Springer Workshop proceedings of ECMLPKDD 2025. Double-submission of research papers is forbidden.

3. Non-archival submissions presenting relevant work recently accepted or currently under submission/review at other venues. The original work should be submitted (free format), enriched with a cover page reporting information on why the manuscript is of interest for the workshop. These submissions will not be included in the Springer Workshop proceedings. Non-archival submissions do not require anonymization unless the authors choose to do so because the paper is currently under review at another venue.

We encourage all qualified candidates to submit a paper regardless of age, gender, sexual orientation, religion, country of origin, or ethnicity. All accepted papers will be presented as posters and linked to the workshop page. Submitting a paper to the workshop means that if the paper is accepted at least one author should present it at the workshop. The best contributions will be allocated a 15 min presentation during the workshop to maximize their visibility and impact.

Key Dates:

• Paper Submission Deadline: 14 June 2025

• Paper Author Notification: 14 July 2025

• Workshop date: 15 or 19 September 2025

How to submit:

TBD

Workshop Chairs

Andrea Passerini

Associate Professor at the Department of Information Engineering and Computer Science (DISI) of the University of Trento and Adjunct Professor at Aalborg University. He is director of the Structured Machine Learning Group and coordinator of the Research Program on Deep and Structured Machine Learning, both at DISI. His research interests include structured machine learning, neuro-symbolic integration, explainable and interactive machine learning, preference elicitation and learning with constraints. He co-authored over 140 refereed papers, and he regularly publishes at top ML and AI conferences and journals like NeurIPS, ICLR, ECMLPKDD, IJCAI, AAAI, MLJ, AIJ and DAMI. He co-organized ECMLPKDD in 2016, AIxIA in 2018, PAIS in 2022 and several workshops and tutorials at top machine learning and AI conferences.

See Andrea's Webpage

Burcu Sayin

Postdoctoral Researcher at the Department of Information Engineering and Computer Science (DISI) of the University of Trento. Her research interests include hybrid human-machine intelligence, natural language processing, trustworthy AI, cost-sensitive machine learning, and active learning. She serves as a reviewer for top ML and AI conferences like ICML, AAAI, ACL, ECAI, and The WebConf. She contributed to organizational roles in international conferences and workshops, such as HCOMP 2023, CI 2023, and ECMLPKDD 2023. She co-organized the first and second edition of HLDM workshop.

See Burcu's Webpage

Anna Monreale

Associate Professor at the Department of Computer Science of the University of Pisa and an Adjunct Professor at the Faculty of Computer Science of the Dalhousie University. She is vice-coordinator of the National PhD in Artificial Intelligence for the Society of the University of Pisa. Her research interests include Big Data Analytics, Artificial Intelligence, Privacy-by-Design in big data and AI, and Explainable AI. She co-authored over 140 refereed papers published at top ML and AI conferences and journals like ECMLPKDD, SIGKDD, AAAI, DAMI, Artificial Intelligence, and Intelligent Systems. She co-organized several workshops and tutorials at top machine learning and AI conferences.

See Anna's Webpage

Catholijn Jonker

Professor in Artificial Intelligence at TU Delft and Leiden University. She is president of ICT Platform of the Netherlands, board member of the Centre for Bold Cities, principal investigator of the Amsterdam Institute of Advanced Metropolitan Solutions (AMS), and vice-coordinator of the Hybrid Intelligence Centre. She is a member of the Royal Holland Society of Sciences and Humanities, a Fellow of EurAI, and member of the Academia Europaea. She is a co-founding member of the Netherlands Academy of Engineers. She served as board member and president of IFAAMAS, and has been programme chair and general chair of the AAMAS conference. Her research expertise is on hybrid intelligence, decision support systems and multi-agent systems.

See Catholijn's Webpage

Jie Yang

Assistant professor in the Web Information Systems (WIS) group at TU Delft. He co-leads the Kappa research line on Crowd Computing \& Human-Centered AI and manage the GENIUS lab that researches Generative AI development and usage in large organizations. He develops human-centered computing for trustworthy machine learning, especially for natural language processing. His research contributes a new set of human-in-the-loop methods and tools that leverage human conceptual and perceptual abilities for understanding machine decisions and for guiding the decisions to better align with human values. With such efforts, his utmost goal is to transform machine learning into an engineering discipline that gives humans full control of AI such that it can be reliably and safely used in various contexts.

See Jie's Webpage

Contact

For any information please contact hldm-workshop@unitn.it