Business Process Management Foundations and Engineering
The Business Process Management: foundations and engineering (BPM) group is a group in the Informatik i9 chair of the RWTH Aachen University. The focus of the BPM group is on the combination of data-based process analysis and the optimisation of processes in organisations.


2024ss Master course: fundamentals of business process management

In this Master course, we will provide a broad introduction into business process management (BPM), and cover several areas of BPM in depth, such as process modelling, process analysis, process mining and process redesign. After this course, you’ll be able to apply business process management strategies to organisations, to communicate business processes in formal modelling notation, to analyse a process running in an actual organisation, propose improvements to the process, and use process data to substantiate your findings. Finally, you are able to communicate your findings in a corporate-appropriate style.

Previously offered: 2023ws, 2023ss, 2022ws.
Next offering: 2024ws.

2024ws Bachelor course: Business Process Modelling & Computation

In this Bachelor course, we will dive into the art of modelling business processes, and how to use computation to assess the performance and quality of business process models.

Previously offered: 2023ws.
Next offering: 2024ws.

2024ss Bachelor & Master seminar: reliability in process mining

Process mining is a field of research that produces software and methodologies to optimise processes in organisations using recorded information. Analysts use process mining tools to analyse this information. For instance, bottlenecks, inefficiencies and optimisation opportunities may be identified. As large investment decisions may be based on these conclusions, it is of vital importance that the accuracy of process mining insights can be established, and that analysts can trust what the software indicates. This may have both technical and organisational aspects.

In this seminar, we are studying the accuracy and reliability of process mining techniques.

Previously offered: 2023ws.

2024ss Master seminar: probabilities in process mining

Process mining aims to provide insights into business processes. Compared to "regular" process mining, process mining that focuses on probabilities considers how often behaviour was seen in event logs. After all, the relevance of behaviour depends on its likelihood. Recently, many such "stochastic" process mining techniques have been proposed. In this seminar, each participant will dive into and discuss a topic in stochastic process mining.

The seminar involves choosing a topic, presenting the ideas of the paper in a presentation, and writing a short report. The presentations will take place in a session starting in the second half of the semester.

Previously offered: 2023ws.

2024ss Software lab: process mining with frequencies using Rust

This software lab course is designed to enable students to get hands-on experience with developing process mining techniques. This course includes the implementation of existing stochastic process mining algorithms to either discover process models or to enable other types of analyses, in particular existing frequency-based (stochastic) techniques. The students will work in a group and follow the Software Development Lifecycle. All meetings will be offered online.

The group

Office E2356-6009 to 6011
Ahornstrasse 55
52074 Aachen, Germany
Consultation hour Every Tuesday 16:00-17:00
Zoom link on request

Sander Leemans

Group lead.

Born in Boxtel, the Netherlands, Univ-Prof. Dr. Ir. Sander J.J. Leemans is a professor (W2) at the Rheinisch-Westfälische Technische Hochschule University (RWTH), Aachen, Germany.

His research interests include process mining, process discovery, conformance checking, stochastic process mining, and robotic process automation. In particular, he specialises in making solid academic techniques available to end-users, analysts and industry partners. He teaches business process management, business process modelling and business process improvement.

Personal website
Additional engagements Fraunhofer Gesellschaft

Tian Li

Scientific employee.

Tian Li is a joint PhD student at RWTH Aachen University and the University of Melbourne. His research focuses on stochastic process mining. At RWTH, he is actively engaged in courses Fundamentals of Business Process Management, Business Process Modelling & Computation, Reliability in Process Mining, and Advanced Topics in Stochastic Process Mining.

Additional engagements: University of Melbourne

Niklas van Detten

Scientific employee.

Additional engagements: Celonis

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