My name is prof.dr.ir. Boudewijn van Dongen and I am full Professor in Computer Science at Eindhoven University of Technology.


Contact me at:

P.O. box 513, 5600 MB, Eindhoven, The Netherlands

Room: Metaforum 7.103

b.f.v.dongen@tue.nl

About my research group

I am full professor in Process Analytics and chair of the Analytics for Information Systems group at Eindhoven University of Technology, a research group with six senior researchers, over 15 PhD candidates.


The research group distinguishes itself in the Information Systems discipline by its fundamental focus on modelling, understanding, analyzing, and improving processes.


The research in the our group continues to expand outward from a classical situation of data with clear case notions in the context of explicitly structured processes to a broad, multi-faceted field, where processes are less structured or consist of many interacting artifacts and where case notions in data become more fluid or are complex, multi-dimensional networks.

My personal interest is in 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. I aim to develop techniques and tools to analyze databases and logs of large-scale information systems for the purpose of detecting, isolating, diagnosing and predicting misconformance in the business processes supported by these systems.


The notion of alignments play a seminal role in conformance checking and the AIS group is world-leading in the definition of alignments for various types of observed behavior and for various modelling languages.


Next to the theoretical foundations, I also develop the tools to actually measure conformance. These tools are typically implemented in Java in the open-source framework ProM. While Java is the language of choice for sake of openness to the larger process mining community, my code typically contains what is sometimes described as "bit-porn", i.e. C-style data structures and bitwise operations, compressing memory to the maximum to make tools applicable to larger and larger datasets.