Within the BPR4GDPR EU project, we are researching (among others) methods that enable a privacy-aware utilization of sensitive individual information. Several anonymization techniques are not enough to completely keep the process discovery completely privacy aware (e.g. the existence of rare diseases can still be revealed from an anonymized log file). Adding exactly “the correct amount” of Read More …
Zaman, R., & Hassani, M. (2019). Process mining meets GDPR compliance: the right to be forgotten as a use case. In B. van Dongen, & J. Claes (Eds.), ICPM Doctoral Consortium 2019: Proceedings of the ICPM 2019 Doctoral Consortium co-located with 1st International Conference on Process Mining (ICPM 2019) (CEUR Workshop Proceedings; Vol. 2432). CEUR-WS.org. Read More …
Hassani, M. (2019). Concept drift detection of event streams using an adaptive window. In 33rd International ECMS Conference on Modelling and Simulation, ECMS 2019 (pp. 230-239). [DSM 73] (Proceedings – European Council for Modelling and Simulation, ECMS; Vol. 33). Abstract Process mining is an emerging data mining task of gathering valuable knowledge out of the Read More …
Position: PhD Student Room: MF 7.122 Tel (internal): 6320 Links: Courses Presentations Projects Publications External links: TU/e page Recent courses Recent presentations Recent projects Recent publications
Boudewijn’s research focusses on conformance checking. Conformance checking is considered to be anything where observed behavior, needs to be related to already modeled behavior. Conformance checking is embedded in the larger contexts of Business Process Management and Process Mining. Boudewijn aims to develop techniques and tools to analyze databases and logs of large-scale information systems Read More …
In the context of the EU H2020 project BPR4GDPR (Business Process Re-engineering and functional toolkit for GDPR compliance), a PhD position is open at the Process Analytics (PA) group in TU/e’s Department for Mathematics and Computer Science in the domain of Model Adaptability. Position PhD-student Department(s) Department of Mathematics & Computer Science Institutes Data Science Read More …
In the context of the EU H2020 project BPR4GDPR (Business Process Re-engineering and functional toolkit for GDPR compliance), a PhD position is open at the Process Analytycs (PA) group in TU/e’s Department for Mathematics and Computer Science in the domain of Stream Process Mining. Position PhD-student Department(s) Department of Mathematics & Computer Science Institutes Data Read More …
Business Process Re-engineering for General Data Protection Regulation Description The goal of BPR4GDPR is to provide a holistic framework able to support end-to-end GDPR-compliant intra- and interorganisational ICT-enabled processes at various scales, while also being generic enough, fulfilling operational requirements covering diverse application domains. To this end, proposed solutions will have a strong semantic foundation Read More …
Dr. Marwan Hassani is assistant professor at the PA group with a focus on Real-Time Process Mining. His research interests include stream data mining, sequential pattern mining of multiple streams, efficient anytime clustering of big data streams and exploration of evolving graph data. He uses customer journey optimizationa and privacy-aware process mining as use cases for his Read More …
Position: UD Room: MF 7.146 Tel (internal): 4144 Links: Courses External assignments Projects Publications External links: Scopus page DBLP page TU/e page Recent courses Recent external assignments Recent projects Recent publications
Position: PhD Student Room: MF 7.108 Tel (internal): 6322 Links: Courses Presentations Projects Publications External links: TU/e page Recent courses Recent presentations Recent projects Recent publications
Eric is the scientific programmer in the PA group. As such, he is the custodian of the process mining framework ProM. In you want access to the ProM repository, or have any questions related to ProM and its development, as Eric. Recently, he has been working on a decomposition framework for both process discovery as Read More …
