Academic Alliance

Celonis for Researchers

Celonis and academia are strong partners in research. Whether you want to use our technology to evaluate your data or you would like to be at the forefront of applied Process Mining research with us, we are happy to support and collaborate.

Celonis is involved in a wide range of research projects with its Academic Partners across multiple disciplines. Collaboration can range from knowledge exchange workshops over thesis projects with graduate students all the way to large multi-year projects.

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StockSnap 0K2OHEKTRH
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Execution Management System - Academic Edition

All-in-one Platform for Process Excellence

  1. Free: For students, teachers, and researchers
  2. All Celonis features: Event Collection, Process Analytics, ML Workbench, Action Engine
  3. Data: Preloaded demo data and flexible data uploads
  4. Campus feeling: Designed for use in classroom and self-learning

Why to Research with Celonis

Join our ecosystem

Become part of the Celonis ecosystem with 130,000+ active Process Miners from all types of organizations and industries.

Use leading technology

Run your applied research projects on the fastest cloud plattform for Process Mining and access Celonis development features.

Work with industry experts

Work side-by-side with industry experts and academia to expand your research.

Research Program

Research Projects with Academic Alliance Partners

Celonis works on joint research projects with academic partners, as well as in consortia with industry partners. Through these research projects we are laying a long-term foundation for our product development and at the same time opening up new fields of application for the process mining technology.

Would you also like to do research with us? Contact us with a pitch of your project idea and we will contact you. For smaller projects a direct cooperation within the scope of knowledge exchange workshops or student theses is conceivable. Celonis can also participate in projects on state level (Free State of Bavaria), federal level (e.g., BMBF, BMWi) or EU level. Furthermore, our subsidiaries around the world can act as local project partners.

For our research activities in the year 2020 we were awarded by the Stifterverband.


Publicly funded project consortium with support by the Bavarian Ministry of Economic Affairs, Regional Development and Energy

Period: Aug 2020 - Dec 2022
Partners: Technical University of Munich, iwb, Mechanical Engineering (Institute for Machine Tools and Industrial Management), HAWE Hydraulik SE

The aim of ProVSA is to develop a procedure that allows value streams in production to be digitally analyzed. Based on value stream analysis, predictive and prescriptive approaches are to be further developed, which support production planning.


Publicly funded project consortium with support by the Bavarian Ministry of Economic Affairs, Regional Development and Energy

Period: Sep 2020 - Aug 2023
Partners: Fraunhofer Institute for Integrated Circuits IIS, AST-X GmbH, Maxsyma GmbH & Co. KG, PASS Stanztechnik AG, Rauschert Heinersdorf-Pressig GmbH

AI4Pro aims at the optimization of spatially distributed processing steps with high variant diversity by developing AI- and CPS-based tools to monitor processes and derive forecasts and recommendations for action.

Indexing Techniques for Variant Clustering

Period: July - Dec 2020
Partner: Prof. Dr. Nikolaus Augsten, Paris Lodron University Salzburg, Austria

In a previous project between the partners, an algorithm for the clustering of process variants has been developed. Using indexing techniques, the performance of this algorithm will be improved.

Wissenschaftliche Veröffentlichungen

Wir forschen gemeinsam mit unseren Academic Alliance Partnern aktiv in allen Themenbereichen des Process Mining. Hier findest du einige unserer Forschungsbeiträge.

Unleashing Digital Process Innovation with Process Mining: Designing a Training Concept with Action Design Research

Proceedings of the European Conference on Information Systems (ECIS 2022). Adrian Joas, Martin Matzner.

Celonis PQL: A Query Language for Process Mining

Process Querying Methods, Artem Polyvyanyy (Ed., 2022). Thomas Vogelgesang, Jessica Kaufmann, David Becher, Robert Seilbeck, Jerome Geyer-Klingeberg, Martin Klenk. Springer.

The Potential of Technology-Mediated Learning Processes: A Taxonomy and Research Agenda for Educational Process Mining

Proceedings of the International Conference on Information Systems (ICIS 2021). Thiemo Wambsganss, Anuschka Schmitt, Thomas Mahnig, Anja Ott, Sigita Soellner, Ngoc Anh Ngo, Jerome Geyer-Klingeberg, Janina Nakladal.

Process Mining at Lufthansa CityLine: The Path to Process Excellence

Journal of Information Technology Teaching Cases (2021). Markus Böhm, Julian Rott, Julia Eggers, Philipp Grindemann, Janina Nakladal, Maximilian Hoffmann, Helmut Krcmar.

Managing the Interpretive Flexibility of Technology: A Case Study of Celonis and its Partner Ecosystem

Proceedings of the International Conference on Information Systems (ICIS 2021). Martin Engert, Yifang Chu, Andreas Hein, Helmut Krcmar.

Celonis Studio – A Low-Code Development Platform for Citizen Developers

Proceedings of the Business Process Management Conference (BPM 2021). Carolin Ullrich, Teodora Lata, Jerome Geyer-Klingeberg.

Scaling Density-Based Clustering to Large Collections of Sets

Proceedings of the 24th International Conference on Extending Database Technology (EDBT 2021). Daniel Kocher, Nikolaus Augsten, Willi Mann.

Co-innovation in a University-Industry Partnership: A Case Study in the Field of Process Mining

1st Workshop on Academy meets Industry in Information System Engineering (AMISE 2020). Fareed Zandkarimi, Janina Nakladal, Josua Vieten, Jerome Geyer-Klingeberg.

Dynamic Pattern-based Case Filters using Regular Expressions

Proceedings of the Business Process Management Conference (BPM 2020). Thomas Vogelgesang, Janina Nakladal, Jerome Geyer-Klingeberg, and Peyman Badakhshan.

Celonis Process Repository: A Bridge between Business Process Management and Process Mining

Proceedings of the Business Process Management Conference (BPM 2020). Peyman Badakhshan, Jerome Geyer-Klingeberg, Muhammad El-Halaby, Thomas Lutzeyer, Gabriela Vianna Lembo Affonseca.

The Action Engine - Turning Process Insights into Action

Proceedings of the 1st International Conference on Process Mining (ICPM 2019). Peyman Badakhshan, German Bernhart, Jerome Geyer-Klingeberg, Janina Nakladal, Steffen Schenk, Thomas Vogelgesang.

From Technical Product Training to Sustainable Education for Students – A Strategic Alliance Approach to Applied MOOCs

Proceedings of EMOOCs 2019. Janina Nakladal, Jerome Geyer-Klingeberg, Matthias Stierle, Martin Matzner.

Process Selection in RPA Projects: Towards a Quantifiable Method of Decision Making

Proceedings of the International Conference on Information Systems (ICIS 2019). Jonas Wanner, Adrian Hofmann, Marcus Fischer, Florian Imgrund, Christian Janiesch, Jerome Geyer-Klingeberg.

Process Mining and Robotic Process Automation: A Perfect Match

Proceedings of the Dissertation Award and Demonstration, Industrial Track at (BPM 2018). Jerome Geyer-Klingeberg, Janina Nakladal, Fabian Baldauf, Fabian Veit.

The Proactive Insights Engine: Process Mining meets Machine Learning and Artificial Intelligence

Proceedings of the Business Process Management Conference (BPM 2017). Fabian Veit, Jerome Geyer-Klingeberg, Julian Madrzak, Manuel Haug, Jan Thomson.

Wil van der Aalst BG BANNER
Wil van der Aalst

“Process mining is one of the rare examples where a new category of software tools can be directly linked to university research. Therefore, it is interesting to reflect on the relationship between industry and academia.”

Wil van der Aalst
Distinguished Humboldt Professor and Chief Academic Advisor of Celonis
RWTH Aachen University and Fraunhofer-Institut for Applied Information Systems
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