New PhD student: Minshuo Li
On October 1st, 2024, Minshuo Li started as a PhD student in the PA group. He will be working under the supervision of Wim Nuijten, A big welcome to Minshuo!
On October 1st, 2024, Minshuo Li started as a PhD student in the PA group. He will be working under the supervision of Wim Nuijten, A big welcome to Minshuo!
Minshuo Li is a Ph.D. student at Eindhoven University of Technology – Data Science Domain – Process Analytics cluster. He works under the supervision of prof. dr. ir. Wim Nuijten. Position: PhD Room: Tel (internal): Links: External links: TU/e page Recent courses Recent presentations Recent projects Recent publications
Today, September 30st, ProM 6.14 has been released. This is the first release of ProM for which GitHub was used during development.
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 …
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 …
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
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 …
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
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 …
Objectives The winter school will bring students together from different technical majors to work jointly on a business development process, where they learn to: Apply practical tools and templates to extend their entrepreneurial skills Analyse a business case and propose a domain plan and business plan Raise self-awareness by reflecting on their motivations, ambitions and 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 In this meeting the student gets insight into the study program.
Objectives In this meeting the student gets insight into the study program.
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 In this meeting the student gets insight into the study program.
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 …
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 …
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 …
The Study & Career Orientation Program is intended to support the students in a structured way in their decision-making process towards graduation with a research group of their preference and to prepare students for making choices regarding their future career. The program is mandatory for all students in the DSAI, CSE, IST and ES programs Read More …
Objectives At the end of the Preparation Phase the student is able to (context [C], research question [Q] and project preparation [P]): [C1] summarize and discuss the problem context, domain-knowledge, and the requirements these set [C2] demonstrate an understanding of and discuss the relevant state-of-the-art in research and other prior work in academia (and the organization). [Q1] formulate one or more research questions relevant with respect to the given context and state-of-the-art 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 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 …
Objectives After taking this course students should: have a good understanding of process mining, understand the role of data science in today’s society, be able to relate process mining techniques to other analysis techniques such as simulation, business intelligence, data mining, machine learning, and verification, be able to apply basic process discovery techniques to learn Read More …
Objectives Acquire state-of-the-art scientific knowledge of a particular topic in the information systems domain. Typical topics are process modeling, workflow management, process mining, web services, service oriented architectures, language transformations, etc. Content People interested in the ‘process side’ of information systems can take the course ‘Capita selecta architecture of information systems’. This course will be Read More …
Verbeek, E., & Fahland, D. (2023). Generating Event Logs with CPN IDE. In Doctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023 (CEUR Workshop Proceedings; Vol. 3648). Abstract This extended abstract introduces the event log generation facility of CPN IDE. CPN IDE has replaced CPN Tools as a tool 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 …
Ozkan, B., Koops, M., Türetken, O., & Reijers, H. A. (2023). The Influence of Business Process Management System Implementation on an Organization’s Process Orientation: A Case Study of a Financial Service Provider. Information Systems Management, 1-22. Advance online publication. https://doi.org/10.1080/10580530.2023.2286980 Abstract This study investigates the influence of Business Process Management System (BPMS) implementation on an Read More …
Spenrath, Y., Hassani, M., & van Dongen, B. F. (2024). Online Prediction Threshold Optimization Under Semi-deferred Labelling. In T. Palpanas, & H. V. Jagadish (Eds.), 8th International workshop on Data Analytics solutions for Real-LIfe APplications (DARLI-AP) (CEUR Workshop Proceedings; Vol. 3651). CEUR-WS.org. https://ceur-ws.org/Vol-3651/ Abstract In supermarket loyalty campaigns, shoppers collect stamps to redeem limited-time luxury 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 …
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 …
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!
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 …
Fahland, D., Fournier, F., Limonad, L., Skarbovsky, I., & Swevels, A. J. E. (2024). How well can large language models explain business processes? arXiv, abs/2401.12846. https://doi.org/10.48550/arXiv.2401.12846 Abstract Large Language Models (LLMs) are likely to play a prominent role in future AI-augmented business process management systems (ABPMSs) catering functionalities across all system lifecycle stages. One such Read More …
Swevels, A., Fahland, D., & Montali, M. (2024). Implementing Object-Centric Event Data Models in Event Knowledge Graphs. In J. De Smedt, & P. Soffer (Eds.), Process Mining Workshops – ICPM 2023 International Workshops, 2023, Revised Selected Papers (pp. 431-443). (Lecture Notes in Business Information Processing; Vol. 503 LNBIP). https://doi.org/10.1007/978-3-031-56107-8_33 Abstract Recent advances in object-centric process Read More …
Mozafari Mehr, A. S. (2024). Multi-perspective Conformance Checking: Identifying and Understanding Patterns of Anomalous Behavior. [Phd Thesis 1 (Research TU/e / Graduation TU/e), Mathematics and Computer Science]. Eindhoven University of Technology. Summary The problem of anomaly detection in business process executions has high level of complexity. On one hand, detecting deviating behavior requires considering various Read More …
van Delft, R. A. J. J., & de Carvalho, R. M. (2022). Using Machine Learning Techniques to Support the Emergency Department. Computing and Informatics, 41(1), 154-171. https://doi.org/10.31577/CAI_2022_1_154 Abstract This research lays down foundations for a stronger presence of machine learning in the emergency department. Using machine learning to make predictions on a patient’s situation can Read More …
Verdaasdonk, M. J. A., & de Carvalho, R. M. (2022). From predictions to recommendations: Tackling bottlenecks and overstaying in the Emergency Room through a sequence of Random Forests. Healthcare Analytics, 2, Article 100040. https://doi.org/10.1016/j.health.2022.100040 Abstract One of the goals to improve the quality of care in hospitals is to set a maximum of four hours Read More …
Benzarti, I., Mili, H., Medeiros de Carvalho, R., & Leshob, A. (2022). Domain engineering for customer experience management. Innovations in Systems and Software Engineering, 18(1), 171-191. https://doi.org/10.1007/s11334-021-00426-2 Abstract Customer experience management (CXM) denotes a set of practices, processes, and tools, that aim at personalizing a customer’s interactions with a company around the customer’s needs and Read More …