Department of Advanced Computing Sciences


The Department of Advanced Computing Sciences is Maastricht University’s largest and oldest department broadly covering the fields of artificial intelligence, data science, computer science, mathematics and robotics.

Over 100 researchers work in the department, whose roots trace back to 1987. 

About us

Research area groups

Our research area groups foster collaboration and knowledge exchange between colleagues working on similar methods. Researchers move freely between these groups, which themselves evolve according to the latest advances in the various branches of computing sciences.

Each research area group is led by a dedicated coordinator.

Current research area groups and coordinators

Director of research:  Nava Tintarev
Chair: Mark Winands

Department of Advanced Computing Sciences

Professors and chairs

Distinguished university professor

Prof. dr. Michel Dumontier: Data Science | View profile
Prof. Dumontier's research focuses on the development of novel computational methods for responsible data science and artificial intelligence with applications computational drug discovery and personalized medicine. This includes developing approaches in formal knowledge representation (knowledge graphs), machine and deep learning (predictive models and synthetic data), and data quality and data sharing (FAIR principles).

Full professors

Prof. dr. Adriana (Anda) Iamnitchi: Computational Social Sciences | View profile
Prof. Iamnitchi’s research efforts focus on developing and applying computational approaches to extract knowledge from massive amounts of data in order to analyze, model and simulate users’ collective and individual behavior on cyber-social systems.

Prof. dr. ir. Ralf Peeters: Mathematical Aspects of Knowledge Engineering | View profile
The focus of Prof. Peeters' chair is on data-driven methods of mathematical modelling, control and optimization, including signal and image processing and machine learning. Applications lie in health, systems biology, engineering and industry.

Prof. dr. Frank Thuijsman: Strategic Optimisation and Data science | View profile
Research focus is on dynamic (evolutionary) game theory particularly and on operations research (planning and scheduling) more generally. Applications in the bio(medical) domain on the one hand and the industrial domain on the other are a driving force on Prof. Thuijsman's research agenda, and AI tools are used for data analysis.

Prof. dr. Nava Tintarev: Explainable Artificial Intelligence | View profile
As AI systems’ actions and decisions will significantly affect their users, it is important to be able to understand how and why an AI system produced the effect that it did. One key aim of Prof. Tintarev's chair is therefore to make the inner workings of AI systems more accessible and transparent in a human-understandable way.

Prof. dr. Gerhard Weiss: Artificial Intelligence and Computer Science | View profile
This chair’s research focus is on automated knowledge processing and on theoretical foundations and practical applications of intelligent systems. Prof. Weiss is particularly interested in the design and analysis of methods and techniques that enable such systems to cooperate and compete with each other in a flexible and autonomous way.

Prof. dr. Anna Wilbik: Data Fusion and Intelligent Interaction | View profile
This chair bridges the gap between the meaning of data and human understanding in complex application environments, where data can be of various natures. Prof. Wilbik’s research focus lies on supporting interaction between machine and human for joint decision-making, information and data fusion, and decision contextualizing.

Prof. dr. Mark Winands: Machine Reasoning | View profile
Machine Reasoning involves algorithms to efficiently search in general solution spaces, and methods specifically for planning and scheduling, game theory, reasoning under uncertainty, adaptive strategies, and constraint satisfaction. This chair operates on the interface of AI and Mathematics and Operations Research, as many of these algorithms originate from the latter.

Professors holding endowed chairs

Prof. dr. Christopher Brewster: Application of Emerging Technologies | View profile
The chair in Application of Emerging Technologies is supported by TNO.
Prof. Brewster's research interests include Semantic Technologies, Open and Linked Data, Interoperability Architectures and Data Governance, with a focus on food and agriculture, and the wider issues of the impact of technology on the environment.

Prof. dr. David Groep: e-Infrastructure | View profile
The chair in e-Infrastructure is supported by Nikhef.
This chair focuses on the integration of computing systems, networks, and storage; the evolution of algorithms that exploit the novel systems architectures; and the secure collaboration mechanisms that make this a collective, global ecosystem. This e-Infrastructure is then used in data-processing intensive applications to validate the results in real-life.

Prof. dr. Jan Scholtes: Text-Mining | View profile
The chair in Text-Mining is supported by ZyLAB.
Text mining aims to provide deeper understanding and new insights of large collections of textual data as faced in legal, medical, law enforcement, intelligence, social sciences, humanities or marketing applications. Text-mining research applies advanced techniques from the fields of information retrieval (search engines) and advanced natural language processing (NLP).

Maastricht University professors

News, grants and media appearances

Research news

More news items
  • As of 1 April 2022, David Groep holds an endowed chair at the Department of Data Science and Knowledge Engineering. His work revolves around the complex, large-scale ICT infrastructures that provide a foundation for similarly cutting-edge research.

  • Two large consortia of Dutch companies and knowledge institutes in the mobility and transport sector will receive 47 million euros in government funding to realize breakthroughs in electrification and hydrogen applications in automotive, maritime and air transport.

Researchers in the media

More news items

Memberships, affiliations and networks

Within Maastricht University

Institute of Data Science

Institute of Data Science

The Institute of Data Science (IDS) is committed to research in data science and artificial intelligence, collaborating across disciplines, institutions, and sectors. The goal is to accelerate scientific discovery, improve clinical care and well-being, and to strengthen communities.

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The Institute of Data Science is part of the Department of Advanced Computing Sciences.