Full Professor

Boudewijn van Dongen

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Group / Unit
Information Systems WSK&I
Building
MetaForum
Floor / room
7.103

Research Profile

Boudewijn van Dongen is a full Professor in computer science and chair of the Process Analytics group at Eindhoven University of Technology (TU/e). The research group distinguishes itself in the Information Systems discipline by its fundamental focus on modeling, understanding, analyzing, and improving processes. Boudewijn’s research focuses on conformance checking: anything where observed behavior needs to be related to previously 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 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, he also develops the tools to actually measure conformance. These tools are typically implemented in Java in the open-source framework ProM.

Academic Background

Boudewijn van Dongen obtained his MSc in Computer Science and his PhD in Process Mining and Verification from TU/e in 2003 and 2007 respectively. He is playing a leading role in several projects set up with his group. These include develop new techniques to deal with massive event data, developing novel techniques and tools to analyze software systems in vivo, a long-term strategic cooperation with Philips Research Eindhoven on data science, health and lighting and process mining in logistics at logistics company Vanderlande.

Educational Activities

  • Business process intelligence
  • Business information systems
  • Business process simulation
  • Introduction to process mining
  • Process modeling and simulation
  • Honors part 1 track Big Data

Ancillary Activities

No ancillary activities