Teaching
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.A sub-set of the videos we use for the lectures is available on YouTube.
Previously offered:
2024ss, 2023ws, 2023ss, 2022ws.
Next offering:
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.A sub-set of the videos we use for the lectures is available on YouTube.
Previously offered:
2023ws.
Next offering:
2024ws.
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:
2024ss, 2023ws, 2024ss.
Next offering:
2024ws.
Master seminar: frequencies 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:
2024ss, 2023ws, 2024ss.
Next offering:
2024ws.
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.Previously offered: 2024ss.
Depth-Area Oral Colloquium (Schwerpunktkolloquium)
It is possible to do a depth-area oral colloquium in the BPM group. To this end, you should have at least followed the Fundamentals of Business Process Management course, plus ideally a seminar. To reach the required three courses, you'll need another course from another group, with a second examiner from that respective group.Please note that the PADS chair does not accept depth-area oral colloquia unless all three courses are from their chair. Still, the BPM group can assess Business Process Intelligence and Advanced Process Mining, however we'll need another examiner.
The group
| Office | E2356-6009 to 6011 Ahornstrasse 55 52074 Aachen, Germany |
| Secretariat | +49 241 80 26049
Opening hours: Mon - Tue - Thu: 08:30-12:00 Wed: 08:30 - 16:00 |
| Consultation hour |
Every Tuesday 16:00-17:00
Zoom link on request |
Prof. 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 | https://leemans.ch |
| Additional engagements | Fraunhofer Gesellschaft |
Sabine Offermanns
Secretary.
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.
Niklas is a PhD student at RWTH, and a working student at Celonis. His research focuses on modeling formalisms and process discovery algorithms in the object-centric setting. He is engaged in our courses Fundamentals of Business Process Management, Business Process Modelling & Computation and the BPM Software Lab.
| Additional engagements: | Celonis |
Student projects
Open student projects
- Bachelor or Master project: BYO. Got an idea that lies in the field of the BPM group? Feel free to let us know; if it's interesting, we might consider it.
Previous and ongoing projects
-
2025
- Stochastic BPMN discovery. S.V. (master).
-
2024
- Approximate Inductive Miner Filtering. M.D. (bachelor).
- Conformance Checking (EMSC) in Rust. L.M. In collaboration with i9 - Process and Data Science (bachelor).
- Haskell & Process Mining. P.F. (bachelor).
- Stochastic Process Discovery in Rust. (bachelor).
- Studying online browsing behaviour using process mining. K.S. In collaboration with Leibniz-Institut für Sozialwissenschaften (master).
- Generalised stochastic labelled Petri nets. D.P. In collaboration with i9 - Process and Data Science (master).
- Batching in Process Mining. B.B. In collaboration with Celonis (master).
- Stochastic Conformance Checking with BPMN. A.K. (master).
- Process Mining: Analysing Resources. G.S. (master).
- Adaptive Process Discovery. C.S. (master).
- Querying Infinite Process Models. E.P. (master).
- Object-Centric Properties in Graph Databases. E.W. (master).
- Comparing Process Execution Behavior on Healthcare Data. P.B. In collaboration with Queensland University of Technology (master).
- Process Differences in Power Plants. S.W. In collaboration with Uniper (master).
- Guaranteeing Privacy through Differential Privacy for Healthcare Process Data. H.U. In collaboration with Queensland University of Technology (master).
- Streaming Stochastic Process Discovery. M.H. (master).
- Identifying Objects in Databases. J.E. (master).
- Stochastic BPMN. L.M.
- 2023
- Optimizing Cohort Analysis: Exploring Heuristics for Refined Splits on Numeric Attributes. L.C.
- Identify process differences in Power Plants with the help of Process Mining. L.B. with Uniper
- Stochastic Process Discovery in Python. M.K.
- Enhancing Operational Efficiency through Process Mining and Robotic Process Automation: A Comprehensive Study of Customer Journey and Meter to Cash Processes. D.I. with Stadtwerke Münster
- 2022
- Visualisation of Causal Reasoning over Control-Flow Decisions in Process Models. A.P.
- Comparative Process Mining in Healthcare. A.T. with Queensland University of Technology
- Analysis of the Influence of different Reward and Observation Designs in the Context of Reinforcement Learning for Production Scenarios of Modular Car Body Manufacturing. T.L. with Mercedes-Benz Research
- An Approximate Inductive Miner. N.v.D. with Celonis
- Comparative Process Mining in Healthcare. T.M. with Queensland University of Technology
- Investigating the Impact of Training Workers on Data Quality. H.F. with RWTH Mechanical Engineering
- Visualizing and Discovering Causal Relations to End Users for Optimization of Process Analysis. P.F.
Job openings
None at the moment.Ebi
Ebi is a stochastic process mining software suite, maintained by the BPM group of RWTH.
For more information, see https://ebitools.org.