Celonis for Researchers

Driving innovation through research is a cornerstone of our mission at Celonis. Our teams across all departments and functions are strongly committed to research and collaboration with academia.

In partnership with leading universities, we strive to maintain a strong presence in applied Process Mining research, continuously exploring new avenues for innovation. Since the launch of the Celonis Academic Alliance in 2016, we have jointly worked on over 1,200 student theses and over 90 applied research projects with our academic partners.

We welcome you to explore the opportunities for collaboration in research through partnering with Celonis.

Alliance Research - hero

Our commitment to academic research

Wil van der Aalst BG BANNER
Jeff Naughton Celonis

Process mining relies on (big) data. With our evolving ETL and database infrastructure and process mining-inspired query language (PQL), we are continuously developing cutting-edge technologies to take advantage of the vast amount of process data and knowledge to deliver value for our customers. In our research projects, we are focusing on building ever more scalable and low latency databases and process mining engines.

Jeff Naughton
SVP Engineering and Technical Fellow
WilvanderAalst-bw

Object-centric process mining exemplifies the direct link between pioneering academic research and the emergence of transformative business software. In our research projects, we are working on the next generation of 3D process mining for industry applications.

Wil van der Aalst
Chief Scientist Celonis, Distinguished Humboldt Professor at RWTH Aachen University
Chief Scientist, Celonis
cong-yu-celonis

The AI team at Celonis (CeloAI) focuses on developing new capabilities and applications to solve advanced use cases and deliver outsized values to our customers. We leverage process intelligence (data and knowledge acquired through process mining and modeling) and combine PI with Machine Learning, Decision Intelligence, and Generative AI to enable new solutions, experiences, and intelligent applications. In our research projects, we are also exploring how Generative AI can potentially disrupt process mining, automation, and many other related areas.

Cong Yu
VP Engineering (AI and Knowledge)

Engagement opportunities for students & faculty

Student engagement
  • Celonis Thesis Program: Through our StaR program, we provide support for Bachelor’s and Master’s theses, as well as seminar and capstone projects.

  • Internships: Become an intern with one of our research-focused teams and be a part of the innovation journey at Celonis. Explore our internship opportunities!

Faculty engagement
  • Featured research collaborations: Collaborate with us on bilateral innovation projects.
  • Visiting researchers: Join one of our technical team and drive applied research with us.

Research areas @ Celonis

Process Mining

Our research in Process Mining delves deep into the analysis of real-world processes, uncovering valuable insights to optimize workflows and enhance operational efficiency.

AI

At the intersection of AI and Process Mining, we're pioneering the integration of artificial intelligence to unlock novel use cases, making Process Mining insights readily accessible to non-technical users while driving operational excellence and innovation.

Database

Our database research focuses on creating robust and scalable data management solutions, ensuring secure and efficient data storage, retrieval, and analysis for a wide range of Process Mining applications.

Process Mining

Our research in Process Mining delves deep into the analysis of real-world processes, uncovering valuable insights to optimize workflows and enhance operational efficiency.

AI

At the intersection of AI and Process Mining, we're pioneering the integration of artificial intelligence to unlock novel use cases, making Process Mining insights readily accessible to non-technical users while driving operational excellence and innovation.

Database

Our database research focuses on creating robust and scalable data management solutions, ensuring secure and efficient data storage, retrieval, and analysis for a wide range of Process Mining applications.

Our researchers

Our team of researchers and engineers drive progress in three key research areas: process mining and modeling, artificial intelligence and machine learning, and databases and data analytics.

As an organization, we maintain a portfolio of research projects ranging from fundamental research on technology innovation to applied research on product innovation, while empowering individuals and teams to set their own research agenda. An essential part of our research work is the close collaboration with our academic partners. Celonis was born out of academia and research; disseminating our research in scientific publications, participating in research conferences, and engaging with the scientific community is an essential part of our research philosophy.

Research Publications

We actively contribute to the Process Mining & Execution Management research field and work together with our Academic Alliance Partners in various research projects. Here you can find a selection of our joint publications with academic partners.

Business Miner: Process Mining Insights for Business Users

5th International Conference on Process Mining, ICPM (2024), Carolin Ullrich, Teodora Lata

Polynomial-Time Conformance Checking for Process Trees

Business Process Management: 21st International Conference, BPM (2023), Eduardo Goulart Rocha, Wil M. P. van der Aalst

A Two-Level Signature Scheme for Stable Set Similarity Joins

Proceedings of the VLDB Endowment (VLDB 2023). Daniel Schmitt, Daniel Kocher, Nikolaus Augsten, Willi Mann, Alexander Miller.

Discovering Process-Based Drivers for Case-Level Outcome Explanation

International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) at ICPM (2023). Peng Li, Hantian Zhang, Xu Chu, Alexander Seeliger, Cong Yu.

Bridging the Digital Skills Gap in Accounting: The Process Mining Audit Professional Curriculum and Badge

Accounting Horizons (2023). Scott A. Emett, Marc Eulerich, Katherine Lovejoy, Scott L. Summers, David A. Wood

Transform Business Operations with Process Mining

Harvard Business Review (2023). Lars Reinkemeyer, Tom Davenport.

An Approximate Inductive Miner

Proceedings of the International Conference on Process Mining (ICPM 2023). Jan Niklas van Detten, Pol Schumacher, Sander J. J. Leemans

Creating Business Value with Process Mining

The Journal of Strategic Information Systems 31, 101745 (2022). Peyman Badakhshan, Bastian Wurm, Thomas Grisold, Jerome Geyer-Klingeberg, Jan Mendling, Jan vom Brocke.

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.

Dear visitor, you're using an outdated browser. Parts of this website will not work correctly. For a better experience, update or change your browser.