iCIS focusses on improving the quality of software, with an emphasis on enhancing reliability, security, architectures, and system alignment. The research is organised within three themes: Software Science, Digital Security, and Data Science.
The overall objective of iCIS is to perform excellent scientific research and to have a positive impact in science and also in society — both in terms of improved economic performance and in terms of social well-being. iCIS not only aims to study technical aspects of software systems, but also their embedding in the environments in which they have to operate.
Each of the three research themes (Software Science, Digital Security, and Data Science) of iCIS has its own research focus and aims. These themes build upon Radboud University’s long-standing tradition of combining cutting-edge research on the mathematical foundations of computer science with societally relevant problems that are susceptible to scientific solutions.
Software Science (SwS)
The Software Science group focuses on the use of formal models in the development of computer systems in relationship to application areas, on the one hand, and on the development of the required basic techniques, on the other hand. Our theories, methods, and tools are empirically validated through the development of challenging applications from the industrial, health care, governmental, and financial sectors, thus aiming at bridging the gap between theory and practice. The topics driving the research carried out in the section are models and modelling.
Digital Security (DiS)
Digital security is an increasingly important issue in our society. The Digital Security group works on a broad range of topics in computer security, including applied cryptography, security protocols, smart cards and RFID, and the security and correctness of software. We are also interested in societal aspects of digital security, such as privacy and e-voting, and interaction with disciplines outside computer science such as cryptography and law. Furthermore, the Digital Security group hosts the interdepartmental Information Foraging Lab.
Data Science (DaS)
The focus of the Data Science group lies on machine learning and artificial intelligence in general, with applications to (among others) neuroscience and bioinformatics. They develop theory and methods for scalable machine learning and information retrieval to analyse big data and address challenging problems in science and society. The section is involved in various projects with other groups, both within and outside the Radboud University. Research funding mainly comes from NWO, STW, and the EU.
View all papers, dissertations, and datasets of iCIS in Radboud Repository.
Research Data Management
Research data management (RDM) is about the ways in which research data are collected, stored, protected, and made available for re-use or re-production. The Radboud University highly values clear, accurate, and safe processes of data management.
The specification of the policy tailored towards iCIS, as well as the iCIS data protocol, can be obtained below. For more information, contact the iCIS data management contact person Güneş Acar.