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 …
Seidel, A., Weske, M., Montali, M., Rivkin, A., Reichert, M., van der Werf, J. M. E. M., van der Aalst, W. M. P., Breitmayer, M., Liss, L., van Detten, J. N., Jalali, A., Khayatbashi, S., König, M., Lichtenstein, T., Rinderle-Ma, S., Weber, B., Soffer, P., Rossi, L., Calegari Garcia, D., Delgado, A., Dijkman, R., Winkler, Read More …
Tentina, I., Zerbato, F., Mannhardt, F., & van Dongen, B. F. (2025). Why Do Users Struggle to Get Insights from Process Mining? In J. De Weerdt, J.-R. Rehse, & H. Reijers (Eds.), 2025 7th International Conference on Process Mining, ICPM 2025 Article 11220617 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPM66919.2025.11220617 (best student paper award) Abstract Read More …
Irina Tentina, Francesca Zerbato, Felix Mannhardt and Boudewijn van Dongen have received the Best Student Paper Award at ICPM 2025 for their paper titled “Why do users struggle to get insights from Process Mining?“. Congratulations to Irina, Francesca, Felix and Boudewijn!
Francesca Zerbato has received one of the two Best Reviewer Awards at ICPM 2025. Congratulations to Francesca!
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 …
Tentina, I., Mannhardt, F., Zerbato, F., & van Dongen, B. (2025). Can Users Trust Process Mining? In K. Wecel (Ed.), Business Information Systems: 25th International Conference, BIS 2025, Poznań, Poland, June 25–27, 2025, Proceedings (pp. 137-151). (Lecture Notes in Business Information Processing (LNBIP); Vol. 554). Springer. https://doi.org/10.1007/978-3-031-94193-1_11 Abstract Process mining enables organizations to gain insights Read More …
Have you ever analyzed some event data and wondered if the steps you take impact the results you get?Or whether the result you obtain match what you expected to find? These are common challenges faced by process mining analysts, who analyze large sets of event data to gain insights into how business processes are executed. Read More …
General learning goals Use basic statistical concepts and techniques and perform appropriate statistical tests Choose and apply suitable visualization techniques Analyze and model data using linear regression, clustering, decision tree mining and association rules learning Read and make simple database schemes and simple queries to a database. Clean data, choose and apply data transformations, data Read More …
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 the course, students are able to independently apply and follow established data science research methods for a given problem and data set access, process, and reason about a large, complex dataset given Read More …
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 …
Beerepoot, I., Di Ciccio, C., Reijers, H. A., Rinderle-Ma, S., Bandara, W., Burattin, A., Calvanese, D., Chen, T., Cohen, I., Depaire, B., Di Federico, G., Dumas, M., van Dun, C., Fehrer, T., Fischer, D. A., Gal, A., Indulska, M., Isahagian, V., Klinkmüller, C., … Zerbato, F. (2023). The biggest business process management problems to solve Read More …
Job description Have you ever analyzed some data and wondered whether there were better ways to come to the results?And, have you ever reflected on whether such results actually match with what you expected to find? These are just two of the questions that process mining analysts ask themselves when extracting insights from large event Read More …
On April 15th, Francesca Zerbato started working as an Assistant Professor in the PA group. Francesca will be working with Dirk Fahland on the design, development and evaluation of interactive tools and software artifacts that can support the real needs of human analysts when dealing with complex and knowledge-intensive tasks such as data sense-making. A Read More …
Position: UD Room: MF 7.061 Tel (internal): Links: External links: Google Scholar pageScopus pageTU/e page Francesca Zerbato received her Ph.D. from the Department of Computer Science at the University of Verona (Italy). Her thesis focused on the modeling of temporal aspects and data in business process models under the supervision of Prof. Carlo Combi. After Read More …
Description The AutoTwin project addresses the technological shortcoming and economic liability of the development and usage of digital twins that are accepted as the accelerator and enabler of Circular Economy in businesses and production by conduction research in 3 areas: introducing a breakthrough method for automated process-aware discovery towards autonomous Digital Twins generation, to support Read More …
