Felix Mannhardt

Position: PhD Student
Room: MF 7.117
Tel (internal): 3425
Links: Google scholar page
Scopus page
ORCID page
TU/e employee page

Publications

  • Process mining for healthcare: Characteristics and challenges - Jorge Munoz-gama, Niels Martin, Carlos Fernandez-llatas, Owen A. Johnson, Marcos Sepúlveda, Emmanuel Helm, Victor Galvez-yanjari, Eric Rojas, Antonio Martinez-millana, Davide Aloini, Ilaria Angela Amantea, Robert Andrews, Michael Arias, Iris Beerepoot, Elisabetta Benevento, Andrea Burattin, Daniel Capurro, Josep Carmona, Marco Comuzzi, Benjamin Dalmas, Rene De La Fuente, Chiara Di Francescomarino, Claudio Di Ciccio, Roberto Gatta, Chiara Read More ...
  • Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions - Koorn, J. J., Lu, X., Mannhardt, F., Leopold, H., & Reijers, H. A. (2022). Uncovering Complex Relations in Patient Pathways based on Statistics: the Impact of Clinical Actions. https://doi.org/10.24251/HICSS.2022.503 Abstract Process mining is a family of techniques that can aid healthcare organizations in improving their processes. Most existing process mining techniques do not provide insights Read More ...
  • What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning - Ketykó, I., Mannhardt, F., Hassani, M., & van Dongen, B. F. (2021). What Averages Do Not Tell – Predicting Real Life Processes with Sequential Deep Learning. CoRR, abs/2110.10225. https://arxiv.org/abs/2110.10225 Abstract Deep Learning is proven to be an effective tool for modeling sequential data as shown by the success in Natural Language, Computer Vision and Signal Read More ...
  • Privacy and Confidentiality in Process Mining – Threats and Research Challenges - Elkoumy, G., Fahrenkrog-Petersen, S. A., Sani, M. F., Koschmider, A., Mannhardt, F., Voigt, S. N. V., Rafiei, M., & Waldthausen, L. V. (Accepted/In press). Privacy and Confidentiality in Process Mining – Threats and Research Challenges. ACM Transactions on Management Information Systems, XX(X). https://arxiv.org/abs/2106.00388 Abstract Privacy and confidentiality are very important prerequisites for applying process mining Read More ...
  • Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs - Klijn, E. L., Mannhardt, F., & Fahland, D. (2021). Classifying and Detecting Task Executions and Routines in Processes Using Event Graphs. In A. Polyvyanyy, M. T. Wynn, A. Van Looy, & M. Reichert (Eds.), Business Process Management Forum, BPM 2021, Proceedings (pp. 212-229). (Lecture Notes in Business Information Processing; Vol. 427 LNBIP). https://doi.org/10.5281/zenodo.5091610, https://doi.org/10.1007/978-3-030-85440-9_13 Abstract Business Read More ...
  • Detection of batch activities from event logs - Martin, N., Pufahl, L., & Mannhardt, F. (2021). Detection of batch activities from event logs. Information Systems, 95, [101642]. https://doi.org/10.1016/j.is.2020.101642 Abstract Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this Read More ...
  • Designing a Privacy Dashboard for a Smart Manufacturing Environment - Mannhardt, F., Oliveira, M., & Petersen, S. A. (2020). Designing a Privacy Dashboard for a Smart Manufacturing Environment. In I. O. Pappas, I. O. Pappas, P. Mikalef, L. Jaccheri, J. Krogstie, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Digital Transformation for a Sustainable Society in the 21st Century – I3E 2019 IFIP WG 6.11 International Read More ...
  • Event abstraction in process mining: literature review and taxonomy - van Zelst, S. J., Mannhardt, F., de Leoni, M., & Koschmider, A. (2020). Event abstraction in process mining: literature review and taxonomy. Granular Computing, XX(XX). https://doi.org/10.1007/s41066-020-00226-2 Abstract The execution of processes in companies generates traces of event data, stored in the underlying information system(s), capturing the actual execution of the process. Analyzing event data, i.e., Read More ...
  • 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 ...
  • Framework for process discovery from sensor data - Koschmider, A., Janssen, D., & Mannhardt, F. (2020). Framework for process discovery from sensor data. CEUR Workshop Proceedings, 2628, 32-38. Abstract Process mining can give valuable insights into how real-life activities are performed when extracting meaningful activities instances from raw sensor events. However, in many cases, the event data generated during the execution of a Read More ...

Presentations

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