Artificial Intelligence

Inge Molenaar focuses on the role of artificial intelligence in education. She is interested in the interface between education and technology, and how we can develop personalised systems that are better suited to the needs of students.

Pim Haselager focuses on philosophy, psychology and artificial intelligence (AI). He researches the social implications of using AI and neuroscience. How can we ensure that new technology is used responsibly?

Tom Heskes researches artificial intelligence, machine learning and data science. He uses probability theory and statistics to develop and gain a better understanding of new data science methods. He is also interested in causality: How do you determine the cause and effect of big data?

Marcel van Gerven focuses on the development of artificial intelligence (AI) that is inspired by the way in which the human brain works. This provides the basis for smarter and more efficient brain-based technology.

Iris Hendrickx researches how AI systems can be used in language technology. Her current work includes the development of a computer system that can talk to people - for instance clients in the healthcare sector - about their happiness and health in Dutch.

Helmer Strik conducts research into the speech of language learners and people with people with communicative disabilities, and into the development and use of apps that employ advanced language and speech technology. He is the initiator of NovoLanguage, which develops apps for language learning.

Arjen de Vries researches how large amounts of data - personal data, medical documents, scientific publications, cultural resources and internet data - can be searched more effectively. He develops AI applications that employ the user’s help to identify the right information.

Tibor Bosse conducts research into the development of social artificial intelligence (AI), which involves chatbots and social robots. How can we build machines that people can interact with naturally, so that we can develop communication skills or help people to stop smoking?

Nelleke Oostdijk researches how predefined linguistic patterns can be used to automatically extract information from large amounts of text. For example, with this method, an investigative authority can detect only those tweets that contain threatening language among millions of tweets.

Henk van den Heuvel’s expertise is collecting and storing spoken language in databases. This data is used to train computers to recognise and transcribe speech, which is useful for developing resources for language learners and people who have experienced language attrition.

Bert Kappen’s research focuses on neural networks and machine learning, and the development of self-learning intelligent systems, which, among other things, can assist in locating missing persons. He also explores how quantum technology can be used for machine learning.

Martha Larson looks at how large amounts of data can be explained, for example, by using smarter transcription to index, interpret and search audio more effectively. She also investigates how multimedia in social networks can be anonymised by users.

Djoerd Hiemstra researches federated search systems, which offer an alternative to the existing search engines’ monopolisation of the internet. Combining data from many independent, autonomous search engines, may possibly provide us with better, specialised search results.