The CAISE 2025 conference took place in Vienna this year. The awarded paper explores the possibility of using steady-state detection techniques in process mining to explicitly differentiate between time periods when a process is in a relatively stable state and when it is subject to increased volatility. This distinction helps avoid misleading insights and leads to more accurate results for many downstream process mining tasks. The pre-print can be found here.
Intro
"The Workflow Systems and Technology (WST) research group primarily focuses on process mining, which is the analysis of organizational processes based on data generated during their execution. In this context, the areas of interest of WST members include (but are not limited to):
- Semantics-aware process mining
- Business process simulation
- Studying process change and dynamics
- Predictive process monitoring
- Visualization of process analysis insights,
- Responsible process mining
The analysis techniques we develop are versatile and can be applied to a wide variety of domains, including processes found in commercial enterprises, such as the production of goods or the handling of customer orders, public administration, such as permit-request management, and healthcare settings, where the focus is on the analysis of treatment processes."
News
Runner-up Best Paper Award at CAISE2025
19.06.2025
