We conduct pioneering research in mathematics and computer science, generate new knowledge and convey it to industry and society. We focus on four areas of fundamental research: Algorithms, Data and Intelligent Systems, Cryptography and Security, and Quantum Computing. Below you will find an overview of our research groups. Click on a specific group for more information.
Research within CWI is organized in 15 research groups.
Algorithms and Complexity
Designing quantum software for future quantum computers, using fundamentally different techniques and approaches based on superposition, interference and entanglement.
Developing the next generation of 3D imaging – enabling scientists to look further into objects of all kinds.
By using a fundamental approach for security engineering, we build trust. We study how to secure computational environments in the presence of strong adversaries where we formally model security guarantees such as privacy, integrity, correctness, and more.
Investigating how cryptologic methods can contribute to solving security issues, for example through encryption, digital signatures and secure computation.
A leading data systems research group, active in the broad area of data (management) systems and infrastructure for supporting data science.
Distributed and Interactive Systems
Facilitating and improving the way people access media and communicate with others and the environment, in areas such as wearable technology and smart textiles, immersive media, languages and infrastructures.
We design and apply biologically inspired, self-learning systems to solve complex real-world problems.
Human-Centered Data Analytics
Developing methods and techniques to better support users in accessing information. Working with social scientists and humanities researchers on technology to better interpret complex data.
Intelligent and Autonomous Systems
Studying generic and fundamental mechanisms that enable the emergence of various degrees of organization, intelligence and autonomy in complex systems, and apply them to concrete problems of societal relevance.
Focusing on how computer programs can learn from and understand data, and then make useful predictions based on it, using insights from statistics and neuroscience.
Combining scientific computing with model reduction and machine learning, with particular focus on plasma dynamics in lightning and space weather, and in high voltage and plasma technology.
Networks and Optimization
Developing algorithmic methods to tackle complex optimization problems by combining techniques from mathematics and computer science, with applications in planning, scheduling and routing.
Investigating and developing mathematical methods to simulate and predict real-world phenomena with inherent uncertainties, targeting applications in climate and energy.
Software Analysis and Transformation
SWAT studies software systems: their design, their construction, and their inevitable evolution. Our mission is to learn to understand software systems and to improve their quality. We focus on complexity as the primary quality attribute of software systems.
Developing and studying probabilistic, operational and statistical models to model, describe, and improve communication, energy, information, logistics, and transportation systems.