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.

Research

The seven most recent publications by members of the group:

Process Mining with Exogenous Data. Adam Banham. Queensland University of Technology PhD thesis in press.
Discovering the Influence of Exogenous Data on Decisions in Processes. Adam Banham, Yannis Bertrand, Robert Andrews, Moe Wynn, Sander J.J. Leemans. International Conference on Application and Theory of Petri Nets and Concurrency in press.
paper
Enjoy the Silence, Part II: Probability-Based Queries on Stochastic Labelled Petri Nets. Sander J.J. Leemans, Marco Montali, Timo Gersing, Felix Engelhardt, Natalia Sidorova. International Conference on Application and Theory of Petri Nets and Concurrency in press.
paper
Partially Ordered Stochastic Conformance Checking. Sander J.J. Leemans, Tobias Brockhoff, Wil M.P. van der Aalst, Artem Polyvyanyy. Knowledge and Information Systems 2025.
paper bibtex
The Tikz-BPMN library. Sander J.J. Leemans. The Comprehensive TeX Archive Network 2025.
On Process Discovery Experimentation: Addressing the Need for Research Methodology in Process Discovery. Jana-Rebecca Rehse, Sander J.J. Leemans, Jan Martijn E.M. van der Werf, Peter Fettke. ACM Transactions on Software Engineering and Methodology 2024.
paper bibtex
Ebi - a Stochastic Process Mining Framework. Sander J.J. Leemans, Tian Li, Jan Niklas van Detten. International Conference on Process Mining Demo Track 2024.
Best Demo award paper presentation bibtex

For the full overview, please see https://leemans.ch/publications/.

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: 2024sw, 2024ss, 2023ws, 2023ss, 2022ws.
Next offering: 2025ws.

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: 2024ws, 2023ws.
Next offering: 2025ws.

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: 2024ws, 2024ss, 2023ws, 2024ss.
Next offering: 2025ss.

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: 2024ws, 2024ss, 2023ws, 2024ss.
Next offering: 2025ss.

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.
Next offering: 2025ss.

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
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

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
- Conformance Checking (EMSC) in Rust. L.M. In collaboration with i9 - Process and Data Science (bachelor).
- Visualizations for Object-Centric Process Trees . P.A.D.P. (bachelor).
- Stochastic BPMN Discovery. L.O. (bachelor).
- Object-Centric Discovery through Case Notions. P.F. (bachelor).
- Discovery of Stochastic BPMN Models. J.D. (bachelor).
- Guided Object-Centric Case Exploration. R.S. (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).
- Stochastic Conformance Checking with BPMN. A.K. (master).
- Stochastic BPMN discovery. S.V. (master).
- Process Mining: Analysing Resources. G.S. (master).
- Developing Heuristc Fallthroughs for the Inductive Miner. C.S. (master).
  thesis
- Sampling in Process Mining. M.M. (master).
- Stochastic Conformance Checking with Partial Trace Matching. P.M. (master).
- Process Mining with Exogenous Data. A.B. In collaboration with Queensland University of Technology (phd).
2024
- Approximate Inductive Miner Filtering. M.D. (bachelor).
- Haskell & Process Mining. P.F. (bachelor).
  thesis
- Stochastic Process Discovery in Python. M.A.K. (bachelor).
- Optimizing Cohort Analysis: Exploring Heuristics for Refined Splits on Numeric Attributes. L.J.C. (bachelor).
- Batching in Process Mining. B.B. In collaboration with Celonis (master).
- Querying Infinite Process Models. E.P. (master).
- Object-Centric Process Mining using Graphs. 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).
  thesis
- Enhancing Operational Efficiency through Process Mining and Robotic Process Automation: A Comprehensive Study of Customer Journey and Meter to Cash Processes. D.I. In collaboration with Stadtwerke Münster (master).
- Identify process differences in Power Plants with the help of Process Mining. L.B. In collaboration with Uniper (master).
2023
- Investigating the Impact of Training Workers on Data Quality. H.F. In collaboration with RWTH Mechanical Engineering (bachelor).
- 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.N.L. In collaboration with Mercedes-Benz Research (bachelor).
- Visualizing and Discovering Causal Relations to End Users for Optimization of Process Analysis. P.F. (master).
- An Approximate Inductive Miner. J.N.V.D. In collaboration with Celonis (master).
- Comparative Process Mining in Healthcare. A.T. In collaboration with Queensland University of Technology (master).
- Visualisation of Causal Reasoning over Control-Flow Decisions in Process Models. A.P. (master).
- Seeing the Forest for the Trees: Stochastic Process Discovery. T.L. In collaboration with University of Melbourne (phd).
- Object-Centric Process Mining. J.N.V.D. In collaboration with Celonis (phd).
2022
- Comparative Process Mining in Healthcare. T.M. In collaboration with Queensland University of Technology (master).

Job openings

None at the moment.

Software

The BPM group maintains several pieces of software, packages and tools.

Ebi is a stochastic process mining software suite. For more information, see https://ebitools.org.
Tikz-bpmn is a Latex Tikz library to draw BPMN models. For more information, see https://ctan.org/pkg/tikz-bpmn.
Visual Miner is a process mining tool that combines several process mining techniques in a single graphical package. For more information, see http://visualminer.org.