Professor Wil van der Aalst at PAIS Lab

Prof. dr.ir. Wil van der Aalst Academic supervisor of the PAIS Lab Professor at the Eindhoven University of Technology (TU/e) Prof. Wil van der Aalst is the academic supervisor of HSE’s International Laboratory of Process-Aware Information Systems. He is also a full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e) and an adjunct professor at Queensland University of Technology (QUT). His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. Wil van der Aalst has published more than 150 journal papers, 17 books (as author or editor), 300 refereed conference/workshop publications, and 50 book chapters. Many of his papers are highly cited (he has an H-index of 101 according to Google Scholar, making him the European computer scientist with the highest H-index) and his ideas have influenced researchers, software developers, and standardization committees working on process support. He has been a co-chair of many conferences including the Business Process Management conference, the International Conference on Cooperative Information Systems, the International conference on the Application and Theory of Petri Nets, and the IEEE International Conference on Services Computing. He is also editor/member of the editorial board of several journals, including the Distributed and Parallel Databases, the International Journal of Business Process Integration and Management, the International Journal on Enterprise Modelling and Information Systems Architectures, Computers in Industry, Business & Information Systems Engineering, IEEE Transactions on Services Computing, Lecture Notes in Business Information Processing, and Transactions on Petri Nets and Other Models of Concurrency. In 2012, he received the degree of doctor honoris causa from Hasselt University. He is also a member of the Royal Holland Society of Sciences and Humanities (Koninklijke Hollandsche Maatschappij der Wetenschappen) and the Academy of Europe (Academia Europaea).
Process Mining: Beyond Control-Flow (PAIS Lab Seminar)
November 24^th, 2014 - 18:10 - aud. 402		Add to Calendar
Thus far the focus of most process mining approaches has been on control-flow, i.e., the ordering of activities. Now that there are mature techniques to discover control-flow models from event logs and to align models (discovered or hand-made) and reality, it becomes more interesting to also incorporate other perspectives such as data, resources, time, etc. This triggers the need for decision mining, organizational mining, and bottleneck mining. This talk will sketch these challenges and put these into the context of the L* life-cycle model for process mining. The L* life-cycle model is comparable to CRISP-DM and SEMMA, but tailored towards process mining. What is still missing is a more detailed cookbook for process mining. One can still find process mining researchers that do not have any idea on how to approach a process mining project. Process mining is apparently still more of an art than a science. This can only be addressed by conducting many real-life process mining projects in a structured and holistic manner. Focusing on a particular control-flow problem is simply not enough. Slides: tbd
Process Mining: Data Science in Action (CSF Colloquium)
November 27^th, 2014 - 16:40 - aud. 317 (lecture hall Descartes)		Add to Calendar
Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive. It is not sufficient to focus on data storage and data analysis. The data scientist also needs to relate data to process analysis. Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). Example applications include: analyzing treatment processes in hospitals, improving customer service processes in a multinational, understanding the browsing behavior of customers using a booking site, analyzing failures of a baggage handling system, and improving the user interface of an X-ray machine. All of these applications have in common that dynamic behavior needs to be related to process models. Hence, prof. Wil van der Aalst refers to it in his talk as "data science in action". Process mining provides not only a bridge between data mining and business process management; it also helps to address the classical divide between "business" and "IT". Evidence-based business process management based on process mining helps to create a common ground for business process improvement and information systems development. Slides: tbd

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Professor Wil van der Aalst at PAIS Lab