Prof.dr.ir. Hajo Reijers is a part-time, full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e). He is also a full professor in Business Informatics at VU University Amsterdam. He is also affiliated to the TiasNimbas Business School, where he is involved as one of the core lecturers in the Executive Master of Operations and Supply Chain Excellence (MOS) program. Hajo Reijers is one of the founders of the Business Process Management Forum, a Dutch platform for the development and exchange of knowledge between industry and academia. Hajo Reijers received a PhD degree in Computer Science (2002), an MSc in Computer Science (1994), and an MSc in Technology and Society (cum laude) (1994), all from TU/e. Hajo Reijers wrote his PhD thesis while he was a manager with Deloitte. Previously, he also worked for Bakkenist Management Consultants and Accenture. As a consultant, he has been involved in various reengineering projects and workflow system implementations, particularly for governmental agencies and organizations offering financial services. From 2012 to 2014, Hajo Reijers headed the BPM R&D group of Perceptive Software. The focus of Hajo Reijers’ academic research is on business process redesign, workflow management, conceptual modeling, process mining, and simulation. On these topics, he published over 150 scientific papers, chapters in edited books, and articles in professional journals.
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Recent external assignments
- Automatically Matching Requirements to Process Models Determining the Impact of Change (ACCHA) - Target audience: Computer Science students with a data science/machine learning/NLP background. Task description: The main task of this Master thesis is to develop and implement a technique that is able to automatically link textual requirements to model-based representations of business process (so-called process models). By doing so, it will be possible to quantify the impact Read More ...
- The Effectiveness of Workflow Technology - Download as PDF
- What’s the name of the game? - Download as PPTX
- TACTICS - TACTICS – Techniques for the Analysis of Client-Team InteraCtionS Description In various care and service settings (e.g. mental healthcare, youth care, social work), teams of professionals interact with clients to improve their well-being. The TACTICS project aims at the development of automated techniques to generate insights into the evolving statuses of such clients as well Read More ...
- Connecting databases with process mining: a meta model and toolset - González López de Murillas, E., Reijers, H. A., & van der Aalst, W. M. P. (2019). Connecting databases with process mining: a meta model and toolset. Software and Systems Modeling, 18(2), 1209-1247. https://doi.org/10.1007/s10270-018-0664-7 Abstract Process mining techniques require event logs which, in many cases, are obtained from databases. Obtaining these event logs is not a Read More ...
- Case notion discovery and recommendation: automated event log building on databases - de Murillas, E. G. L., Reijers, H. A., & van der Aalst, W. M. P. (Accepted/In press). Case notion discovery and recommendation: automated event log building on databases. Knowledge and Information Systems. https://doi.org/10.1007/s10115-019-01430-6 Abstract Process mining techniques use event logs as input. When analyzing complex databases, these event logs can be built in many ways. Read More ...
- Process mining on databases: extracting event data from real-life data sources - Gonzalez Lopez de Murillas, E. (2019). Process mining on databases: extracting event data from real-life data sources Eindhoven: Technische Universiteit Eindhoven
- What if process predictions are not followed by good recommendations? - Dees, M., de Leoni, M., van der Aalst, W. M. P., & Reijers, H. A. (2019). What if process predictions are not followed by good recommendations? In J. vom Brocke , J. Mendling, & M. Rosemann (Eds.), 17th International Conference on Business Process Management 2019 Industry Forum: Proceedings of the Industry Forum at BPM 2019 Read More ...
- Business process improvement activities: differences in organizational size, culture, and resources - Beerepoot, I., van de Weerd, I., & Reijers, H. A. (2019). Business process improvement activities: differences in organizational size, culture, and resources. In T. Hildebrandt, B. F. van Dongen, M. Röglinger, & J. Mendling (Eds.), Business Process Management – 17th International Conference, BPM 2019, Proceedings (pp. 402-418). (Lecture Notes in Computer Science (including subseries Lecture Read More ...
- Using Hidden Markov Models for the accurate linguistic analysis of process model activity labels - Leopold, H., van der Aa, H., Offenberg, J., & Reijers, H. A. (2019). Using Hidden Markov Models for the accurate linguistic analysis of process model activity labels. Information Systems, 83, 30-39. DOI: 10.1016/j.is.2019.02.005 Abstract Many process model analysis techniques rely on the accurate analysis of the natural language contents captured in the models’ activity labels. Read More ...
- Who is behind the model? classifying modelers based on pragmatic model features - Burattin, Andrea, Soffer, Pnina, Fahland, Dirk, Mendling, Jan, Reijers, Hajo A., Vanderfeesten, Irene, Weidlich, Matthias & Weber, Barbara (2018). Who is behind the model? classifying modelers based on pragmatic model features. In Ingo Weber, Jan vom Brocke, Marco Montali & Mathias Weske (Eds.), Business Process Management – 16th International Conference, BPM 2018, Proceedings (pp. 322-338). Read More ...
- A hybrid approach for aspect-oriented business process modeling - Jalali, A., Maggi, F.M. & Reijers, H.A. (2018). A hybrid approach for aspect-oriented business process modeling. Journal of Software : Evolution and Process, 30(8):e1931 Abstract Separation of concerns has long been an important strategy to deal with complexity when developing a system. Some concerns (like security) are scattered through the whole system, and different modules Read More ...
- Multi-perspective process mining - Mannhardt, F. (2018). Multi-perspective process mining. Eindhoven: Technische Universiteit Eindhoven. ((Co-)promot.: Hajo Reijers, Wil van der Aalst & Massimiliano de Leoni).
- Automatic root cause identification using most probable alignments - Koorneef, M., Solti, A., Leopold, H. & Reijers, H.A. (2018). Automatic root cause identification using most probable alignments. In M. Weidlich & E. Teniente (Eds.), Business Process Management Workshops – BPM 2017 International Workshops, Barcelona, Spain, September 10-11, 2017, Revised Papers (pp. 204-215). (Lecture Notes in Business Information Processing, No. 308). Springer. Abstract In many Read More ...