Remco Dijkman
Department / Institute
Group
RESEARCH PROFILE
Remco Dijkman is Full Professor in Information Systems and chair of the Information Systems group at Eindhoven University of Technology (TU/e). His research focuses on Business Process Management and in particular data-driven optimization of business processes. His focus topics are the detection, diagnosis and prediction of optimal execution scenarios, mathematical models for quantitative analysis of business processes, and resource assignment optimization. He mainly looks at applications in transportation and in high-tech supply chains, where his current interests are the use of data-driven predictions to improve transport order assignment and supply chain planning.
ACADEMIC BACKGROUND
Remco Dijkman received his PhD in computer science from the University of Twente. He holds a Master from the same university. Remco has published over 100 papers in scientific journals, conferences and workshops. His work appeared in Information Systems, Computers in Industry and Transactions on Software Engineering and Methodology. He serves on the editorial board of Information Systems. Remco has been a visitor of New York University, Hasso Plattner Institute, IBM Zurich Research Lab, Humboldt-University Berlin, and Queensland University of Technology. He has been involved in a large number of research projects, including as project manager of the GET Service European Project. Currently, he is involved in the DynaPlex, CERTIF-AI, SLEM, and FENIX projects. He also serves as research director high-tech supply chain of the European Supply Chain Forum, a networking organization with over 50 multinational companies as its members.
Key Publications
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Sander Peters,Yoav Kerner,Remco Dijkman,Ivo Adan,Paul Grefen
Fast and accurate quantitative business process analysis using feature complete queueing models
Information Systems (2022) -
Volkan Gumuskaya,Willem van Jaarsveld,Remco Dijkman,Paul Grefen,Albert Veenstra
Integrating stochastic programs and decision trees in capacitated barge planning with uncertain container arrivals
Transportation Research. Part C: Emerging Technologies (2021) -
Amirreza Farahani,Laura Genga,Remco M. Dijkman
Tackling Uncertainty in Online Multimodal Transportation Planning Using Deep Reinforcement Learning
(2021) -
Sudhanshu G.R. Chouhan,Anna M. Wilbik,Remco M. Dijkman
A Real-Time Method for Detecting Temporary Process Variants in Event Log Data
(2021)
Ancillary Activities
- Adjunct Professor, Queensland University of Technology