Process-Oriented Information Systems

Organizations create value through their processes, from handling customer orders and settling insurance claims to granting permits and treating patients. How well these processes run largely determines costs, speed, service quality, and compliance, yet in practice they rarely unfold as designed. Fortunately, the information systems that support processes record each step as it is performed. Process mining uses this event data to reveal how processes are actually executed, where they deviate from expectations, where time and resources are lost, and what is likely to happen next.

The POIS group, led by Univ.-Prof. Han van der Aa, Ph.D., is part of the Research Group Workflow Systems and Technology (WST). We develop techniques that push process mining beyond abstract, descriptive analysis: methods that understand what process steps mean, that turn insights into action, that remain reliable as processes evolve, and that are applied responsibly. To this end, we combine process mining with methods from data management, machine learning, natural language processing, and simulation.

• Semantics-aware process mining: using NLP and large language models to exploit the meaning of process data, e.g., instruction-tuning LLMs for process mining tasks, detecting semantic anomalies
• Process extraction from text: automatically deriving process knowledge from documents and other natural-language sources, e.g., text-to-process extraction with small language models, prompting strategies for process model extraction
• Conformance checking: efficiently detecting and explaining where process executions deviate from their specifications, e.g., discovering process-level deviation patterns, sampling and approximation for efficient conformance checking
• Predictive and prescriptive process monitoring: anticipating how running cases will unfold and determining how to intervene, e.g., calibrated, uncertainty-aware remaining time prediction, inter-case-aware prediction using queuing networks
• Process change and dynamics: detecting and characterizing how processes evolve over time, e.g., concept drift detection using computer vision (BPM 2024 Best Student Paper Award), version clustering for drift detection
• Business process simulation: deriving simulation models from event data to support reliable what-if analysis, e.g., agent-based process simulation, threats to the validity of data-driven simulation
• Event data quality and preparation: ensuring that event data forms a sound basis for analysis, e.g., constraint-driven abstraction of low-level event logs, steady-state detection for more accurate insights
• Visualization and sense-making: helping analysts interpret and act on process mining results, e.g., visual comparative analysis of process variants, a context framework for sense-making
• Responsible process mining: safeguarding privacy and fairness when analyzing data about people, e.g., semantics-aware control-flow anonymization, optimal event log sanitization

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We receive far more requests than we can accommodate, so please read the following before getting in touch. Due to the volume of requests, we cannot respond to generic or mass emails.

• Open positions: Funded PhD and postdoc positions are advertised on the University of Vienna job portal and on Prof. Van der Aa's LinkedIn page. In Austria, PhD candidates are typically employed on funded positions, so we can only take on new PhD candidates when funding is available, and the number of positions is limited. Please apply through the advertised positions rather than sending unsolicited applications.
• Bachelor's and master's theses, P1/P2 projects: Please check our open topics. Since demand greatly exceeds our capacity, approach us well before your intended start. When applying, include your transcript of records and preferably a CV. You are welcome to propose your own project idea, as long as it fits the research topics listed above.
• Visiting researchers: Researchers and PhD candidates interested in a research stay with our group are very welcome. Please contact Prof. Van der Aa with a brief description of your research interests, the intended period of your stay, and how it would be funded (e.g., Erasmus+ or a scholarship from your home institution).
• External PhD candidates: If you are interested in pursuing an external PhD on the above or related topics, for instance while employed in industry, please contact Prof. Van der Aa with your CV and a short outline of your intended research direction. As with internal positions, external PhDs require secured funding, typically through your employer.
• Industry partners: Organizations interested in joint research, such as applying our techniques to their process data or co-supervising theses, are welcome to contact Prof. Van der Aa.

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• Univ.-Prof. Han van der Aa, PhD (Head of the team)
• Dr. Martin Kabierski (Post-doctoral researcher)
• Sana Dodangeh (PhD candidate)
• Bernold Rodrigo Abarca Zuniga (PhD candidate)
• Robert Blümel (External PhD candidate, funded by and working for SAP Signavio)
• Anna Hegler (External PhD candidate)
• Sara Latifi, PhD (Research technician)

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• Selin Ada (Erasmus+ student intern; Ostim Technical University, TR; July 2026 - August 2026)
• Giacomo Acitelli (Visiting PhD candidate; Sapienza University of Rome, IT; May 2025 - July 2025)
• María Salas Urbano (Visiting PhD candidate; University of Seville, ES; January 2025 - April 2025)
• Anton Yeshchenko (Post-doctoral researcher; May 2025 - May 2026)

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• Dr. Alexander Kraus (at the University of Mannheim, DE; thesis defended in November 2025)
• Dr. Adrian Rebmann (at the University of Mannheim, DE; thesis defended in June 2024)

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