Prof.dr.ir. Wil van der Aalst is a full professor of the Process and Data Science (PADS) group at the RWTH in Aachen (Germany) and a part-time professor in the PA group. His personal research interests include process mining, business process management, workflow management, Petri nets, process modeling, and process analysis.

Position:	HGL
Room:	MF 7.064
Tel (internal):	4295
Links:	Personal home page Google scholar page Scopus page ORCID page TU/e page DSC/e

Awards

• BPM Test-of-Time Award at BPM 2023 for Massimiliano de Leoni, Wil van der Aalst and Marcus Dees - Massimiliano de Leoni, Wil van der Aalst, and Marcus Dees have received the BPM Test-of-Time Award at BPM 2023 for their paper titled “A General Framework for Correlating Business Process Characteristics“.
• Test of Time award at BPM 2021 for Dirk Fahland - Dirk Fahland won the Test of Time award for the paper “Repairing Process Models to Reflect Reality” (co-authored by Wil van der Aalst, see also the journal version of this paper). Congratulations to Dirk!
• Best Paper award at ICPM 2020 for Zahra Toosinezhad - Zahra Toosinezhad, Dirk Fahland, and Wil van der Aalst have won the Best Paper award at ICPM with her paper “Detecting System-Level Behavior Leading To Dynamic Bottlenecks“. Congratulations to Zahra , Dirk, and Wil!
• Best PhD. Dissertation award at ICPM 2020 for Xixi Lu - Xixi Lu, a former PhD student of our group, has won the Best PhD. Dissertation award with her thesis “Using behavioral context in process mining: exploration, preprocessing and analysis of event data“. Her promotor was Wil van der Aalst, and Dirk Fahland was one of her copromotors.

Projects

• RISE BPM - “Propelling Business Process Management by Research and Innovation Staff Exchange” Description RISE_BPM is the first favourably evaluated project proposal submitted by the University of Münster in cooperation with ERCIS partners within the Horizon 2020 EU funding programme. The RISE_BPM project is aimed at networking world-leading research institutions and corporate innovators to develop new horizons for Read More ...
• Process Mining in Logistics - Process Mining in Logistics is a joint project of the Data Science Center Eindhoven and Vanderlande industries. Description Logistics processes are notoriously difficult to design, analyze, and to improve. Where classical processes are scoped around the processing of information associated to a specific unique case, logistics deals with physical objects that are grouped and processed Read More ...
• Philips Flagship - Description The Data Science Centre Eindhoven (DSC/e) is TU/e’s response to the growing volume and importance of data and the need for data & process scientists (http://www.tue.nl/dsce/). The DSC/e has recently started a long-term strategic cooperation with Philips Research Eindhoven on three topics: data science, health and lighting. As a first concrete action, 70 PhD Read More ...
• DSC/e & NWO Graduate Program - Data Science Center Eindhoven Description Recent technological and societal changes led to an explosion of digitally available data. Exploiting the available data to its fullest extent, in order to improve decision making, increase productivity, and deepen our understanding of scientific questions, is one of today’s key challenges. Data science is an emerging area that aims Read More ...
• DeLiBiDa - Desire Lines in Big Data Description The goal of process mining is to extract process-related information from event logs, e.g., to automatically discover a process model by observing events recorded by some information system. Despite recent advances in process mining there are still important challenges that need to be addressed. In particular with respect to Read More ...
• Core - CORE – Consistently Optimised REsilient secure global supply-chains Description The CORE project aims to produce cost effective, fast and robust solutions for worldwide Global Supply Chain system. The project will implement an ecosystem where interoperability, security, resilience and real-time are optimized. The role of the AIS group in the project is to employ process mining Read More ...

Publications

• Object-centric process management: A research manifesto - Seidel, A., Weske, M., Montali, M., Rivkin, A., Reichert, M., van der Werf, J. M. E. M., van der Aalst, W. M. P., Breitmayer, M., Liss, L., van Detten, J. N., Jalali, A., Khayatbashi, S., König, M., Lichtenstein, T., Rinderle-Ma, S., Weber, B., Soffer, P., Rossi, L., Calegari Garcia, D., Delgado, A., Dijkman, R., Winkler, Read More ...
• Process science: the interdisciplinary study of socio-technical change - vom Brocke, J., van der Aalst, W. M. P., Berente, N., van Dongen, B. F., Grisold, T., Kremser, W., Mendling, J., Pentland, B. T., Roeglinger, M., Rosemann, M., & Weber, B. (2024). Process science: the interdisciplinary study of socio-technical change. Process Science, 1(1), Artikel 1. https://doi.org/10.1007/s44311-024-00001-5 Abstract Process science is the interdisciplinary study of socio-technical Read More ...
• Challenges of Anomaly Detection in the Object-Centric Setting: Dimensions and the Role of Domain Knowledge - Berti, A., Jessen, U., van der Aalst, W. M. P., & Fahland, D. (2024). Challenges of Anomaly Detection in the Object-Centric Setting: Dimensions and the Role of Domain Knowledge. arXiv.org. https://doi.org/10.48550/arXiv.2407.09023 Abstract Object-centric event logs, allowing events related to different objects of different object types, represent naturally the execution of business processes, such as ERP Read More ...
• The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs] - Wynn, M. T., Van Der Aalst, W., Verbeek, E., & Di Stefano, B. (2024). The IEEE XES Standard for Process Mining: Experiences, Adoption, and Revision [Society Briefs]. IEEE Computational Intelligence Magazine, 19(1), 20-23. https://doi.org/10.1109/MCI.2023.3333141 Abstract The IEEE Standards Association (SA) officially published the XES Standard as IEEE Std 1849-2016: IEEE Standard for eXtensible Event Stream Read More ...
• Towards a Simple and Extensible Standard for Object-Centric Event Data (OCED) – Core Model, Design Space, and Lessons Learned - Fahland, D., Montali, M., Lebherz, J., van der Aalst, W. M. P., van Asseldonk, M., Blank, P., Bosmans, L., Brenscheidt, M., Di Ciccio, C., Delgado, A., Calegari, D., Peeperkorn, J., Verbeek, E., Vugs, L., & Wynn, M. T. (2024). Towards a Simple and Extensible Standard for Object-Centric Event Data (OCED) – Core Model, Design Space, Read More ...
• Explainable Object-Centric Anomaly Detection: the Role of Domain Knowledge - Berti, A., Jessen, U., van der Aalst, W. M. P., & Fahland, D. (2024). Explainable Object-Centric Anomaly Detection: the Role of Domain Knowledge. In BPM-D 2024: Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Forum at BPM 2024 co-located with 22nd International Conference on Business Process Management (BPM 2024) Krakow, Poland, Read More ...
• The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them - Bakullari, B., Thoor, J. V., Fahland, D., & Aalst, W. M. P. v. d. (2023). The Interplay Between High-Level Problems and the Process Instances that Give Rise to Them. In BPM (Forum) (pp. 145-162) https://doi.org/10.1007/978-3-031-41623-1_9
• Process mining for healthcare: Characteristics and challenges - Jorge Munoz-gama, Niels Martin, Carlos Fernandez-llatas, Owen A. Johnson, Marcos Sepúlveda, Emmanuel Helm, Victor Galvez-yanjari, Eric Rojas, Antonio Martinez-millana, Davide Aloini, Ilaria Angela Amantea, Robert Andrews, Michael Arias, Iris Beerepoot, Elisabetta Benevento, Andrea Burattin, Daniel Capurro, Josep Carmona, Marco Comuzzi, Benjamin Dalmas, Rene De La Fuente, Chiara Di Francescomarino, Claudio Di Ciccio, Roberto Gatta, Chiara Read More ...
• Special issue on business process intelligence - Burattin, A., De Weerdt, J., van Dongen, B., Claes, J., & van der Aalst, W. (2021). Special issue on business process intelligence. Computing, 103, 1-2. https://doi.org/10.1007/s00607-020-00856-z
• Inferring Unobserved Events in Systems With Shared Resources and Queues - Fahland, D., Denisov, V., & van der Aalst, W. M. P. (2021). Inferring Unobserved Events in Systems With Shared Resources and Queues. Fundamenta Informaticae, 183(3-4), 203-242. https://doi.org/10.3233/FI-2021-2087 Abstract To identify the causes of performance problems or to predict process behavior, it is essential to have correct and complete event data. This is particularly important for Read More ...

Presentations

• Process Cubes - Download as PDF