This is the list of the workshop co-located with ICPM 2024.

Workshops highlighted with the  FullyInteractive  badge are fully interactive workshops.

BuzzOs- What’s the buzz with objects?  FullyInteractive 

Organized by Andrey Rivkin (DTU, Denmark), Jan Martijn van der Werf, (Utrecht University, The Netherlands)

A new object-centric paradigm has been one of the hottest topics in the Business Process Management and Process Mining communities since a couple of years. But do we all have a common understanding of what object centricity is about? How do we in general interpret the objects in the context of Process Mining? BuzzOs is a fully interactive workshop that aims at answering these questions and challenges whoever is interested in the topic to join forces in setting up a research agenda in the area of object-centric process mining for the years to come.


COMINDS – COllaboration MINing for Distributed Systems

Organized by Lorenzo Rossi (University of Camerino, Italy), Mahsa Pourbafrani (RWTH Aachen University, Germany), Laura González (Universidad de la República, Uruguay)

The Third Workshop on Collaboration Mining for Distributed Systems (CoMinDS 2024) aims to promote the development of innovative techniques for analyzing collaboration processes in distributed scenarios. In real-world situations, where processes are often interconnected and sharing event data might be impractical due to reasons like privacy constraints, the workshop underscores the necessity for creative federated techniques. In real-world situations e.g., supply chains involving manufacturers, producers, and retailers; healthcare scenarios involving patients, hospitals, and doctors; or even smart systems like multi-robot and IoT systems, processes are interconnected, and sharing event data might be impractical due to reasons like privacy constraints. The workshop underscores the necessity for creative techniques facilitating comprehensive process analysis among different parties.


EdbA – Event Data & Behavioral Analytics (EdbA)

Organized by Benoît Depaire (Hasselt University, The Netherlands), Dirk Fahland (TU/Eindhoven, The Netherlands), Francesco Leotta (Sapienza Università di Roma, Italy), Arik Senderovich (York University, Canada)

The EdbA workshop aims to provide a forum for discussing and developing analytics for various forms of event data. In its most basic form, such data describes discrete events, which occur instantly – and thus have no duration, are ordered in time and are described by a set of attributes. The analytical potential of event data lies in the fact that it captures the dynamic behavior of people, objects and/or systems at a fine-grained level. The workshop welcomes both original research papers as well as high-quality case studies on event data and behavioral analytics.


EduPM – Education meets Process Mining

Organized by Jorge Munoz-Gama (Pontificia Universidad Catòlica de Chile), Francesca Zerbato (TU/Eindhoven, The Netherlands), Gert Janssenswillen (Hasselt University, Belgium), Wil van der Aalst (RWTH Aachen University, Germany)

Process Mining has proven to be a powerful interdisciplinary tool for addressing open challenges in several fields such as healthcare or finances … and Education is no exception. The recent Process Mining approaches proposed for learning analytics, curricular analytics, or MOOC analytics are just some examples. But the Education discipline is also contributing to Process Mining, providing best practices, lessons learned, and new artifacts for better teaching and assessing Process Mining.The International Workshop on Education meets Process Mining (EduPM) aims at providing a high-quality forum for the intersection of Education and Process Mining.


ERPM – Empirical Research in Process Mining

Organized by Djordje Djurica (Weizenbaum Institute, Germany and BOC Group, Austria), Kateryna Kubrak (University of Tartu, Estonia), Francesca Zerbato (TU/Eindhoven, The Netherlands), Amine Abbad-Andaloussi (University of St. Gallen, Switzerland)

The 1st Workshop on Empirical Research in Process Mining (ERPM 2024) invites researchers and practitioners to explore the field of empirical process mining, focusing on the systematic investigation of real-world applications, user interactions, and organizational impacts of process mining technologies. This workshop aims to deepen the understanding of process mining’s practical implications by showcasing qualitative and quantitative studies, case analyses, and organizational research.

By offering a platform for discussing empirical research in process mining, the workshop supports the exchange of ideas and collaboration among academics and industry professionals, driving the application of empirical methods within the field. The workshop aims to provide participants with an overview of empirical methods used in process mining, inspire rigorous studies, and identify opportunities and challenges in advancing empirical research.


GenAI4PM – Generative Artificial Intelligence for Process Mining

Organized by Maxim Vidgof (Vienna University of Economics and Business, Austria), Alessandro Berti (RWTH Aachen University, Germany), Mohammadreza Fani Sani (Microsoft)

This workshop is dedicated to exploring the integration of Generative AI (GenAI) in process mining. It aims to bring together industry professionals and researchers to discuss novel methodologies, case studies, and the future of GenAI in enhancing business process analysis, improvement, and execution. The workshop seeks submissions on various themes, including process mining tasks using GenAI, process modeling, robotic process automation, and the impact of GenAI on process transformation. It also looks to delve into the integration of GenAI with other advanced technologies such as blockchain and RPA, aiming to advance the field of process mining. Participants will have the opportunity to engage in discussions on short, medium, and long-term goals of GenAI application in process mining, sharing insights on implementation strategies, challenges, and the potential for process improvement. This gathering is an excellent opportunity for companies interested in implementing GenAI in their processes to connect with leading researchers and organizations at the forefront of this exciting integration.


ML4PM – Leveraging Machine learning in Process Mining

Organized by Paolo Ceravolo (Università degli Studi di Milano, Italy), Sylvio Barbon Junior (Università degli Studi di Trieste, Italy), Vincenzo Pasquadibisceglie (University of Bari Aldo Moro, Italy), Annalisa Appice (Università degli Studi di Bari, Italy)

The International Workshop on Leveraging Machine Learning in Process Mining – ML4PM – is a premier event that aims to foster collaboration and innovation in the intersection of machine learning and process mining. Over the past few years, the combination of these two fields has generated a lot of interest, and this workshop provides an excellent opportunity for researchers and practitioners to share their latest findings and explore new directions for future research.

The workshop will feature a diverse range of papers that showcase the latest advances in automated process modelling, predictive process mining, deep learning techniques, and online process mining. These themes reflect the most exciting and promising areas of research at the intersection of machine learning and process mining. By fostering dialogue and collaboration among participants, the workshop aims to catalyze breakthroughs and push the boundaries of what is possible in this exciting and rapidly-evolving field.


PDCW – Process Discovery Contest Workshop  FullyInteractive 

Organized by Eric Verbeek (TU/Eindhoven, The Netherlands)

This year, there will be a workshop around the Process Discovery Contest: The Process Discovery Contest Workshop (PDCW) 2024. In this workshop, every contestant gets to introduce the discovery approach they are using, and to show and discuss discovery results on a number of selected event logs from the contest (preferably, using a live demo). This provides an overview of the current state in the field of (automated) process discovery and where there is room for improvement. It also shows stronger and weaker points of the different approaches. Prior to these presentations, an overview of how the current Process Discovery Contest has been set up will be presented, as well as the ground truth models for the selected event logs. More details will follow later.


PLC – Processes, Laws, and Compliance

Organized by Laura Genga (TU/Eindhoven, The Netherlands), Hugo A. López (DTU, Denmark), Emilio Sulis (University of Turin, Italy)

The Processes, Laws, and Compliance (PLC) workshop intends to provide a forum to facilitate the exchange of research findings and ideas on data-driven and process-oriented techniques and practices in the legal domain, fostering collaboration among interdisciplinary experts, researchers, and practitioners working in IT and law.


PM4S – Process Mining for Sustainability

Organized by István Koren (RWTH Aachen University, Germany), Janina Bauer (Celonis), Nina Graves (RWTH Aachen University, Germany), Birgit Penzenstadler (Chalmers University, Sweden)

The PM4S workshop aims to provide a platform for researchers and practitioners to explore the intersection of process mining and sustainability as well as raise awareness for the potential of process mining for supporting sustainable development. It offers a platform to present work contributing to the topic and foster discussion and collaboration on innovative approaches to enhance the environmental and social implications of business processes.


PODS4H – Process-Oriented Data Science for Healthcare

Organized by Niels Martin (Hasselt University, Belgium), Carlos Fernandez-Llatas (Universitat Politècnica de València, Spain), Owen Johnson (University of Leeds, UK), Marcos Sepúlveda, (Pontificia Universidad Católica de Chile), Jorge Munoz-Gama (Pontificia Universidad Católica de Chile)

The Seventh International Workshop on Process-Oriented Data Science for Healthcare (PODS4H24) provides a high-quality forum for interdisciplinary researchers and practitioners to exchange research findings and ideas on data-driven process analysis techniques and practices in healthcare. We aim to bring together researchers and practitioners in a spirit of collaboration and co-creation. In this way, we have the ambition to move PODS4H research and practice forward, taking into account the distinguishing characteristics and challenges of the healthcare domain.


PQMI – Process Querying, Manipulation, and Intelligence

Organized by Artem Polyvyanyy (The University of Melbourne, Australia), Claudio Di Ciccio (Utrecht University, The Netherlands), Antonella Guzzo (University of Calabria, Italy), Arthur H. M. ter Hofstede (Queensland University of Technology, Australia)

The Ninth International Workshop on Process Querying, Manipulation, and Intelligence (PQMI 2024) endeavors to offer a platform facilitating scholarly discussion and knowledge dissemination within the research and professional community. Process querying combines concepts from Big data and process modeling and analysis with business process intelligence and process analytics to study techniques for retrieving and manipulating models of real-world and envisioned processes to organize and extract process-related information for subsequent systematic use. Process manipulation is concerned with ways to update process representations and knowledge to ensure improvements within real-world business operations. Finally, process intelligence looks for the symbioses effects between artificial intelligence and process mining, encompassing such domains as knowledge representation, automated planning, reasoning, natural language processing, explainable AI, and multi-agent systems. The methods, techniques, and tools intrinsic to these interrelated domains find wide-ranging applications in business process management and process mining, including business process compliance, identification of process vulnerabilities, management of process variances, in-depth analysis of process performance, predictive process monitoring, translation of process models, comparative analysis of process models, detection of anomalous process behaviors, seamless migration of process instances, and facilitation of process standardization and reusability.


SMA4PM – Stream Management & Analytics for Process Mining

Organized by Marwan Hassani (TU/Eindhoven, The Netherlands), Thomas Seidl (LMU, Germany), Ahmed Awad (The British University in Dubai, United Arab Emirates)

SMA4PM workshop aims at promoting the use and development of new techniques to support streaming-based process management and analysis. It brings together practitioners and researchers from several communities: Process Mining, Stream Data Mining (mining time series, evolving graphs and scalable large data mining), Business Process Management, Database Systems and Information Systems with interest in online analysis and optimization of process-aware information systems with time, storage or complexity restrictions. Results of ongoing research, practical experiences and ideas for future research directions are also welcome in a work-in-progress track.