Jana-Rebecca Rehse

University of Mannheim, Universidad de Sevilla

Papers

9

Total Citations

151

H-Index

7

About

Jana-Rebecca Rehse is a researcher whose work sits at the dynamic intersection of business process management (BPM), process mining, robotic process automation (RPA), and artificial intelligence. Her scholarship consistently explores how emerging technologies can enhance organizational processes, making her a distinctive voice in both academic and applied computing communities. Rehse's most influential contribution examines how large language models can tackle BPM tasks, a paper that has garnered an impressive 80 citations since 2024, signaling the field's appetite for AI-driven process solutions. Alongside this, her foundational work on reference data models for process-related user interaction logs — examining how low-level user interactions within information systems can be captured and analyzed — has established important infrastructure for process analytics research. Her interests extend meaningfully into robotic process automation, where she has explored connections with process mining, software validation in regulated industries, and even robot-assisted emergency response, where team communication analytics support increasingly autonomous systems. Her participation in high-profile BPM panel discussions further reflects her role as a community builder shaping the discipline's future directions. Taken together, Rehse's portfolio reveals a researcher dedicated to bridging intelligent automation with rigorous process science.

Research Focus

Key Achievements

7
H-Index
9
Papers
151
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Large Language Models Can Accomplish Business Process Management Tasks
80 citations · 2024
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: University of Mannheim, Universidad de Sevilla

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago