Wil van der Aalst

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

  • 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

  • In-database preprocessing for process mining - Syamsiyah, A. (2020). In-database preprocessing for process mining. Technische Universiteit Eindhoven.
  • Privacy-preserving process mining in healthcare - Pika, A., Wynn, M. T., Budiono, S., ter Hofstede, A. H. M., van der Aalst, W. M. P., & Reijers, H. A. (2020). Privacy-preserving process mining in healthcare. International Journal of Environmental Research and Public Health, 17(5), [1612]. https://doi.org/10.3390/ijerph17051612 Abstract Process mining has been successfully applied in the healthcare domain and has helped to uncover Read More ...
  • Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment - Cheng, L., van Dongen, B. F., & van der Aalst, W. M. P. (2020). Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment. IEEE Transactions on Services Computing, 13(2), 368-380. [8669858]. https://doi.org/10.1109/TSC.2019.2906203 Abstract Process descriptions are used to create products and deliver services. To lead better processes and services, the first step is Read More ...
  • Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones - Bloemen, V., van Zelst, S., van der Aalst, W., van Dongen, B., & van de Pol, J. (Accepted/In press). Aligning observed and modelled behaviour by maximizing synchronous moves and using milestones. Information Systems, XX(XX), [101456]. https://doi.org/10.1016/j.is.2019.101456 Abstract Given a process model and an event log, conformance checking aims to relate the two together, e.g. to Read More ...
  • Visualizing Token Flows Using Interactive Performance Spectra - van der Aalst, W. M. P., Tacke Genannt Unterberg, D., Denisov, V., & Fahland, D. (2020). Visualizing Token Flows Using Interactive Performance Spectra. In R. Janicki, N. Sidorova, & T. Chatain (Eds.), Application and Theory of Petri Nets and Concurrency – 41st International Conference, PETRI NETS 2020, Proceedings (pp. 369-380). (Lecture Notes in Computer Science Read More ...
  • Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources - Denisov, V., Fahland, D., & van der Aalst, W. M. P. (2020). Repairing Event Logs with Missing Events to Support Performance Analysis of Systems with Shared Resources. In R. Janicki, N. Sidorova, & T. Chatain (Eds.), Application and Theory of Petri Nets and Concurrency – 41st International Conference, PETRI NETS 2020, Proceedings (pp. 239-259). (Lecture Notes Read More ...
  • Multi-dimensional performance analysis and monitoring using integrated performance spectra - Denisov, V., Fahland, D., & Van Der Aalst, W. M. P. (2020). Multi-dimensional performance analysis and monitoring using integrated performance spectra. In C. Di Ciccio (Ed.), Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020): Padua, Italy, October 4-9, 2020 (pp. 27-30). Read More ...
  • Detecting system-level behavior leading to dynamic bottlenecks - Toosinezhad, Z., Fahland, D., Köroglu, Ö., & Van Der Aalst, W. M. P. (2020). Detecting system-level behavior leading to dynamic bottlenecks. In B. van Dongen, M. Montali, & M. T. Wynn (Eds.), Proceedings – 2020 2nd International Conference on Process Mining, ICPM 2020 (pp. 17-24). [9230102] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM49681.2020.00014 Abstract Dynamic Read More ...
  • Mining process model descriptions of daily life through event abstraction - Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Mining process model descriptions of daily life through event abstraction. In S. Kapoor, R. Bhatia, & Y. Bi (Eds.), Intelligent Systems and Applications: Extended and Selected Results from the SAI Intelligent Systems Conference (IntelliSys) 2016 (pp. 83-104). (Studies in Computational Intelligence; Read More ...
  • Event abstraction for process mining using supervised learning techniques - Tax, N., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2018). Event abstraction for process mining using supervised learning techniques. In Y. Bi, S. Kapoor, & R. Bhatia (Eds.), Proceedings of the SAI Intelligent Systems Conference (IntelliSys 2016), 21-22 September 2016, London, United Kingdom (pp. 251-269). (Lecture Notes in Networks and Systems; Read More ...

Presentations

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