Rik Eshuis works as an Assistant Professor of Information Systems at  Eindhoven University of Technology, in the Department of  Industrial Engineering & Innovation Sciences (IE&IS), subgroup Information Systems. His key areas of expertise include business process modeling, business process management and business information systems engineering. 

His  research  focuses on data-driven business process management for knowledge-intensive processes, i.e. business processes performed by knowledge workers. The research methodology is design science. Models and modeling languages play an important role. His research is embedded in the Process Engineering cluster of the Information Systems subgroup and is on the interface with the Business Intelligence cluster.

Dr. Rik Eshuis received a PhD in Computer Science from the  University of Twente, where he also received an MSc in Computer Science, with distinction. Before joining TU/e, he was a visiting PostDoc at CRP Henri Tudor and LIASIT, Luxembourg. He was a visiting scholar at IBM Watson Research Center. Since 2019, he leads the TU/e IS research cluster on  Process Engineering. He has published over 50 peer-reviewed journal and conference papers in the area of Information Systems. Rik acts as regular reviewer for several international ISI journals, including ACM Transactions on Software Engineering and Methodology and IEEE Transactions on Software Engineering,  Information and Software Technology, Software and Systems Modeling, and Information Systems. He is a member of the program committee for recent international conferences including BPM, CoopIS, ICSOC, and MODELSWARD. He has served as Programme Chair of IEEE EDOC 2020 and IEEE ECOWS 2008, and as General Chair of IEEE ECOWS 2009. Next, he has organized several workshops on innovative topics in Business Process Management, such as data-centric BPM. 

Knowledge workers need to take interdependent, data-driven decisions in their daily work processes. To improve the efficiency and quality of their work, I develop concepts and techniques for intelligent process management.