Position:	UD
Room:	MF 7.119
Tel (internal):	3425
Links:	Courses External assignments Assignments Presentations Projects Publications
External links:	Personal home page Google scholar page Scopus page ORCID page DBLP page TU/e page

Awards

• Best Paper Award at CAiSE’24 for Eva Klijn, Felix Mannhardt and Dirk Fahland - Eva Klijn, Felix Mannhardt and Dirk Fahland have received the Best Paper Award at CAiSE’24 for their paper titled “Multi-Perspective Concept Drift Detection: Including the Actor Perspective“. Congratulations to Eva, Felix and Dirk!
• Best Paper Award at EdbA 2022 for Felix Mannhardt - Paul Kobialka, Felix Mannhardt, Silvia Lizeth Tapia Tarifa and Einar Broch Johnsen have won the Best Paper Award at the EdbA 2022 workshop for their paper titled “Building User Journey Games from Multi-party Event Logs”. Congratulations to Paul, Felix, Silvia and Einar!
• Best Reviewer Award at ICPM 2022 for Felix Mannhardt - Felix Mannhardt has won the Best Reviewer Award at ICPM 2022. Congratulations to Felix!
• Extensions to the bupaR Ecosystem: An Overview - Janssenswillen, G., Mannhardt, F., Creemers, M., Depaire, B., Jans, M., Jooken, L., Martin, N., & Van Houdt, G. (2020). Extensions to the bupaR Ecosystem: An Overview. In Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020) (pp. 43-46). (CEUR Workshop Proceedings; Vol. Read More ...
• A taxonomy for combining activity recognition and process discovery in industrial environments - Mannhardt, F., Bovo, R., Oliveira, M. F., & Julier, S. (2018). A taxonomy for combining activity recognition and process discovery in industrial environments. In D. Camacho, P. Novais, A. J. Tallón-Ballesteros, & H. Yin (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2018 – 19th International Conference, Proceedings (pp. 84-93). (Lecture Notes in Computer Read More ...
• Best Academic Tool Demo award at ICPM 2020 for Felix Mannhardt - Together with others, Felix Mannhardt has won the Best Academic Demo Tool award at ICPM 2020 with their tool demo “Extensions to the bupaR ecosystem: an overview“. Congratulations to Felix and the others!

Recent courses

• Fundamentals of Process Mining (JBI060) 2024-2025 - Objectives The main learning objective of FPM is to be able to understand the relation between sequential multi-variate event data and processes and, ultimately, to learn how to properly apply data science methods in the context of processes. Specifically, the following learning objectives are intended:  to be able to identify challenges and requirements for using Read More ...
• Seminar Process Analytics (2IMI00) 2024-2025 - Objectives This seminar combines teaching research methods (in preparation for a Master project) with providing students with recent and ongoing research in the area of event data analysis and process analysis. We study recent research articles, book chapters, and Master theses on topics along the entire analysis life-cycle. Through presentation and group discussions, we work Read More ...
• Advanced Process Mining (2AMI20) 2024-2025 - Objectives After taking this course students should be able to: have a detailed understanding of the entire process mining spectrum and the methodology for process mining analysis can derive and pre-process event logs from raw data and have understand and can work with a specialized form of event data such as event knowledge graphs, or Read More ...
• Data Challenge 3 (JBG060) 2024-2025 - Objectives Non Bachelor Data Science wanting to register for this course should reach out to program management via mcs.academic.advisor.bds@tue.nl for formal approval After taking this course students should be able to independently: recognize the phases of data analytics research and divide the research process in these phases familiarize themselves with techniques to understand a complex dataset Read More ...

Recent external assignments

• Event Granularity in User Journeys - Context This project is defined in the scope of the Smart Journey Mining project [1, 9]. The SJM project vision is to increase the quality of services by uniting research on customer journeys and process mining using new developments in logic-based analysis and artificial intelligence. Research in SJM is done together with SINTEF Digital (Norway), Read More ...

Recent assignments

• Privacy Guarantees in Process Discovery - Responsible Process Mining as a topic is introduced in [1]: “The prospect of data misuses negatively affecting our life has led to the concept of responsible data science. It advocates for responsibility to be built, by design, into data management, data analysis, and algorithmic decision-making techniques such that it is made difficult or even impossible Read More ...

Recent presentations

• XESLite: Handling Event Logs in ProM - Download as PDF
• Decision Mining: Discovering Overlapping Rules - Download as PDF
• Data Conformance Checking using Optimal Alignments - Download as PPTX

Recent projects

• Smart Journey Mining: Towards successful digitalisation of services - The digitalisation of our society’s service systems has fundamentally changed the way services are delivered to, and experienced by, humans. Although digital services are supposed to simplify our lives and increase our efficiency, they often frustrate and burden customers, users, and employees. The overall goal is to increase the quality of services and support the Read More ...

Recent publications

• Clinical Event Knowledge Graphs: Enriching Healthcare Event Data with Entities and Clinical Concepts – Research Paper - Aali, M. N., Mannhardt, F., & Toussaint, P. J. (2024). Clinical Event Knowledge Graphs: Enriching Healthcare Event Data with Entities and Clinical Concepts – Research Paper. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 296-308). (Lecture Notes in Business Information Processing; Vol. Read More ...
• Comparing Conformance Checking for Decision Mining: An Axiomatic Approach - Banham, A., ter Hofstede, A. H. M., Leemans, S. J. J., Mannhardt, F., Andrews, R., & Wynn, M. T. (2024). Comparing Conformance Checking for Decision Mining: An Axiomatic Approach. IEEE Access, 12, 60276-60298. Article 10504896. https://doi.org/10.1109/ACCESS.2024.3391234 Abstract Process mining uses historical executions of business processes (as recorded in an event log) to uncover and describe Read More ...
• Customer journeys and process mining – challenges and opportunities - Halvorsrud, R., Mannhardt, F., Prillard, O., & Boletsis, C. (2024). Customer journeys and process mining – challenges and opportunities. In International Conference on Exploring Service Science (IESS 2.4) (Vol. 62, pp. 05002). (ITM Web of Conferences). https://doi.org/10.1051/itmconf/20246205002
• Experience-Based Resource Allocation for Remaining Time Optimization - Padella, A., Mannhardt, F., Vinci, F., De Leoni, M., & Vanderfeesten, I. (2024). Experience-Based Resource Allocation for Remaining Time Optimization. In A. Marrella, M. Resinas, M. Jans, & M. Rosemann (Eds.), Business Process Management: 22nd International Conference, BPM 2024, Krakow, Poland, September 1–6, 2024, Proceedings (pp. 345-362). Article Chapter 20 (Lecture Notes in Computer Science (LNCS); Read More ...
• The Quest for the Comprehensive Customer Journey – A Case Study from a C2C Marketplace - Mannhardt, F., Halvorsrud, R., Meironas, O., & Brurok, L. (2024). The Quest for the Comprehensive Customer Journey – A Case Study from a C2C Marketplace. In Business Process Management: Blockchain, Robotic Process Automation, Central and Eastern European, Educators and Industry Forum (Vol. 527, pp. 451-461). Article Chapter 33 (Lecture Notes in Business Information Processing; Vol. 527). https://doi.org/10.1007/978-3-031-70445-1_33
• Multi-Perspective Concept Drift Detection: Including the Actor Perspective - Klijn, E. L., Mannhardt, F., & Fahland, D. (2024). Multi-perspective Concept Drift Detection: Including the Actor Perspective. In G. Guizzardi, F. Santoro, H. Mouratidis, & P. Soffer (Eds.), Advanced Information Systems Engineering – 36th International Conference, CAiSE 2024, Proceedings (pp. 141-157). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Read More ...
• Event Knowledge Graphs for Auditing: A Case Study - Klijn, E. L., Preuss, D., Imeri, L., Baumann, F., Mannhardt, F., & Fahland, D. (2024). Event Knowledge Graphs for Auditing: A Case Study. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 84-97). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_7 Read More ...
• An Experiment on Transfer Learning for Suffix Prediction on Event Logs - van Luijken, M., Ketykó, I., & Mannhardt, F. (2024). An Experiment on Transfer Learning for Suffix Prediction on Event Logs. In J. De Weerdt, & L. Pufahl (Eds.), Business Process Management Workshops – BPM 2023 International Workshops, Utrecht, The Netherlands, September 11–15, 2023, Revised Selected Papers (pp. 31-43). (Lecture Notes in Business Information Processing; Vol. 492 LNBIP). Springer. Read More ...
• Aggregating Event Knowledge Graphs for Task Analysis - Klijn, E. L., Mannhardt, F., & Fahland, D. (2023). Aggregating Event Knowledge Graphs for Task Analysis. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 493-505). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_36 Abstract Aggregation of event data is a Read More ...
• Building User Journey Games from Multi-party Event Logs - Kobialka, P., Mannhardt, F., Tapia Tarifa, S. L., & Johnsen, E. B. (2023). Building User Journey Games from Multi-party Event Logs. In M. Montali, A. Senderovich, & M. Weidlich (Eds.), Process Mining Workshops – ICPM 2022 International Workshops, Revised Selected Papers (pp. 71-83). (Lecture Notes in Business Information Processing; Vol. 468 LNBIP). Springer. https://doi.org/10.1007/978-3-031-27815-0_6 Abstract To Read More ...