Study level


Master of Philosophy


Vacation research experience scheme


Science and Engineering Faculty

School of Information Systems

Topic status

We're looking for students to study this topic.


Dr Kanika Goel
Associate Lecturer
Division / Faculty
Science and Engineering Faculty
Dr Sander Leemans
Lecturer in Business Process Management
Division / Faculty
Science and Engineering Faculty


Organisations continuously look for opportunities to improve or optimise their business processes.

Process mining aids organisations to derive insights from event data stored in event logs, using advanced techniques that:

  • discover process models
  • verify conformance with rules and regulations
  • show the performance of processes.

As process improvement projects are involved and expensive, typically organisations select a few processes to optimise, using process identification.

Ironically, process identification is a manual task, where KPIs are chosen. Based on these KPIs, a process is selected for improvement.

In this project, we aim to make process identification more data driven, by developing process-mining-in the-large techniques, which target entire organisations rather than individual processes.

Research activities

As part of this research project, you'll be involved in:

  • performing a limited literature scan on process identification and process mining
  • developing new process identification and organisation-wide process mining techniques
  • engaging with industry partners to identify needs and to apply and evaluate the developed techniques
  • introducing a methodology for (semi-)automated process identification.


We aim to develop new techniques, methods and methodologies to:

  • model resources and customers interacting with processes in organisations and discover such models automatically
  • lead to automatic value chain discovery
  • automatically identify process KPIs
  • automatically identify the potential for process improvement in processes
  • provide recommendations for the processes to select for improvement
  • apply the new techniques with our industry partners.

Upon conclusion of the project, we expect to have:

  • a limited overview of the most important related work in process identification and process mining
  • implemented prototypes of the techniques
  • publications detailing the techniques and their evaluation.

Skills and experience

To be considered for the project, we expect you to have:

  • in-depth knowledge of Business Process Management (IFN515/IAB203/IAB320 or similar)
  • familiarity with basic programming.

Familiarity with process mining (IFN650/IAB321) is recommended, but is not mandatory.


You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round



Contact the supervisor for more information.