I am a Junior Professor in the Data and Web Science Group at the School of Business Informatics and Mathematics of the University of Mannheim, funded by the Künstliche Intelligenz Baden-Württemberg initative. In this role, I lead the research group on Process Analytics. As of October 2021, I am also a visiting professor at the LAMSADE at the Université Paris Dauphine.Before joining the University of Mannheim in April 2020, I was an Alexander von Humboldt Fellow at the Humboldt University of Berlin as part of the Databases and Information Systems Group of Matthias Weidlich. In January 2018, I received a PhD degree from the Department of Computer Science of the Vrije Universiteit Amsterdam, supervised by Hajo Reijers and Henrik Leopold. Earlier, I received a MSc. degree in Business Information Systems (2013) as well as a BSc. degree in Industrial Engineering (2010) from the Eindhoven University of Technology. I was a visiting research at the TECHNION – Isreal Institute of Technology in November 2016 and at the Vienna University of Economics and Business from June to August 2013.
My research focuses on the development of automated methods for process analysis, driven by tailored artificial intelligence techniques. Among others, my work has been published at the international conferences on Business Process Management (BPM), Advanced Information System Engineering (CAiSE), and Management of Data (SIGMOD), as well as in journals such as IEEE Transactions on Knowledge and Data Engineering, Decision Support Systems, and Information Systems
- November 2021: Our paper on semantics-aware anonymization of event logs received the best student paper award at ICPM’21.
- October 2021: I will join the LAMSADE at the Université Paris Dauphine in Paris, France, as a visiting professor.
- September 2021: Our latest work on privacy-preserving process mining was accepted for ICPM’21
- June 2021: Our paper on the detection of semantic execution anomalies in business processes has been accepted for Information Systems.
- May 2021: We will be giving a tutorial on declarative process mining at the BPM Conference in September 2021.
- March 2021: Our paper on the efficient integration of remote data in event stream processing was accepted for SIGMOD’21.
- February 2021: Happy to have three papers accepted for CAiSE’21, on semantic event log analysis, recommendations for process modelers, and the recognition of hand-drawn BPMN models.
- November 2020: Our paper on the assessment of compliance between process models and regulatory documents received the best student paper award at ER2020.
- October 2020: Our article on Sampling and Approximation Techniques for Efficient Process Conformance Checking, co-authored with Martin Bauer and Matthias Weidlich, has been accepted to the special issue of Information Systems on selected papers from BPM’19.
- September 2020: Happy to have Alexander Kraus on board at our research chair as the second PhD candidate under my supervision
- July 2020: Joint work with Karolin Winter, Stefanie Rinderle-Ma, and Matthias Weidlich on the assessment of compliance between process models and regulatory documents was accepted for the International Conference on Conceptual Modeling (ER).
- July 2020: Happy to have Adrian Rebmann join our research chair as the first PhD candidate under my supervision
- June 2020: Our article on process conformance checking for partially ordered event data has been accepted for Decision Support Systems, co-authored with Henrik Leopold and Matthias Weidlich.
- June 2020: Joint work with Stephan Fahrenkrog-Petersen and Matthias Weidlich, concerned with privacy-preserving event log publishing, was accepted for the International Conference on Business Process Management.
- April 2020: Our article in IEEE Transactions on Knowledge And Data Engineering (TKDE) on Efficient Process Conformance Checking on the Basis of Uncertain Event-to-Activity Mappings, co-authored with Henrik Leopold and Hajo Reijers, has been published.
- April 2020: I have joined the University of Mannheim as a junior professor in the Data and Web Science Group of the School of Business Informatics and Mathematics