2026 Peter Fettke: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	34	11889	11546	588	575	232	11614

Overview

Peter Fettke is affiliated with the German Research Centre for Artificial Intelligence in Germany. Their research focuses primarily on computer science and business management, with significant contributions to areas such as management information systems, artificial intelligence, industrial and manufacturing engineering, information systems, and management science and operations research.

Their main topics of work include:

Business Process Modeling and Analysis
Service-Oriented Architecture and Web Services
Big Data and Business Intelligence
Explainable Artificial Intelligence (XAI)
Simulation Techniques and Applications
Data Quality and Management
Manufacturing Process and Optimization

Peter Fettke has authored multiple papers across diverse venues, with notable recent publications including:

"Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective," 2024, Annals of Operations Research
"A Multi-Sensor Approach for Digital Twins of Manual Assembly and Commissioning," 2020, Procedia Manufacturing
"Manufacturing execution systems driven process analytics: A case study from individual manufacturing," 2021, Procedia CIRP
"Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium-sized enterprises," 2022, Expert Systems
"Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing," 2020, arXiv (Cornell University)

Frequently publishing venues for Fettke's work include:

arXiv (Cornell University)
Proceedings of the Annual Hawaii International Conference on System Sciences
Universität des Saarlandes
DFKI GmbH, Institut für Wirtschaftsinformatik
KI - Künstliche Intelligenz

They have collaborated extensively with co-authors such as Wolfgang Reisig, Nijat Mehdiyev, Péter Pfeiffer, Maxim Majlatow, and Constantin Houy, reflecting ongoing partnerships in their fields of study.

In addition to articles, Peter Fettke has contributed to book publications, including a work published by Springer Science+Business Media titled "Business Process Management: Blockchain and Robotic Process Automation Forum" in 2021.

Best Publications

Industry 4.0

Heiner Lasi;Peter Fettke;Hans-Georg Kemper;Thomas Feld

5110
Citations
Business Process Modeling Notation

Peter Fettke

594
Citations
Model Driven Architecture (MDA)

Peter Fettke;Peter Loos

534
Citations
Predicting process behaviour using deep learning

Joerg Evermann;Jana-Rebecca Rehse;Jana-Rebecca Rehse;Peter Fettke;Peter Fettke

429
Citations
State-of-the-Art des State-of-the-Art

Peter Fettke

413
Citations
Classification of reference models: a methodology and its application

Peter Fettke;Peter Loos

399
Citations
Empirical research in business process management – analysis of an emerging field of research

Constantin Houy;Peter Fettke;Peter Loos

358
Citations
Business process reference models : Survey and classification

Peter Fettke;Peter Loos;Jörg Zwicker

350
Citations
Business process reference models: survey and classification

Peter Fettke;Peter Loos;Jörg Zwicker

248
Citations
Reference Modeling for Business Systems Analysis

Peter Fettke;Peter Loos

202
Citations
How Conceptual Modeling Is Used

Peter Fettke

165
Citations
ONTOLOGICAL EVALUATION OF REFERENCE MODELS USING THE BUNGE-WAND-WEBER MODEL

Peter Fettke;Peter Loos

136
Citations
Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry

Nijat Mehdiyev;Johannes Lahann;Andreas Emrich;David Lee Enke

134
Citations
A Deep Learning Approach for Predicting Process Behaviour at Runtime

Joerg Evermann;Jana-Rebecca Rehse;Jana-Rebecca Rehse;Peter Fettke;Peter Fettke

131
Citations
Referenzmodellierungsforschung@@@Reference modeling research

Peter Fettke;Peter Loos

113
Citations
A systematic literature review on state-of-the-art deep learning methods for process prediction

Dominic A. Neu;Dominic A. Neu;Johannes Lahann;Johannes Lahann;Peter Fettke;Peter Fettke

103
Citations
Perspectives on Reference Modeling

Peter Fettke;Peter Loos

102
Citations
Multiperspective evaluation of reference models: Towards a framework

Peter Fettke;Peter Loos

99
Citations
Towards an Integrative Big Data Analysis Framework for Data-Driven Risk Management in Industry 4.0

Tim Niesen;Constantin Houy;Peter Fettke;Peter Loos

98
Citations
Report : The Process Model Matching Contest 2013

Ugur Cayoglu;Remco M. Dijkman;Marlon Dumas;Peter Fettke

97
Citations
Understanding understandability of conceptual models --- what are we actually talking about?

Constantin Houy;Peter Fettke;Peter Loos

97
Citations
A Novel Business Process Prediction Model Using a Deep Learning Method

Nijat Mehdiyev;Nijat Mehdiyev;Joerg Evermann;Peter Fettke;Peter Fettke

97
Citations
Evaluating Forecasting Methods by Considering Different Accuracy Measures

Nijat Mehdiyev;Nijat Mehdiyev;David Lee Enke;Peter Fettke;Peter Fettke;Peter Loos;Peter Loos

92
Citations

Frequent Co-Authors

Wil M. P. van der Aalst RWTH Aachen University

Ingo Weber Technical University of Berlin

John Krogstie Norwegian University of Science and Technology

Matthias Weidlich Humboldt-Universität zu Berlin

Marlon Dumas University of Tartu

Remco Dijkman Eindhoven University of Technology

Jan Mendling Humboldt-Universität zu Berlin

Wolfgang Reisig Humboldt-Universität zu Berlin

Alexander Maedche Karlsruhe Institute of Technology

Martin Bichler Technical University of Munich

External Links

Personal website of Peter Fettke

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