Stephan Raaijmakers

POSITION: PROFESSOR | COMMUNICATIVE AI TNO UNIT: INFORMATION & COMMUNICATION TECHNOLOGY (DATA SCIENCE) UNIVERSITY: LEIDEN UNIVERSITY, LUCL (LEIDEN UNIVERSITY CENTER FOR LINGUISTICS)   TNO LOCATION: DEN HAAG, ANNA VAN BUERENPLEIN 1 EMAIL: STEPHAN.RAAIJMAKERS@TNO.NL TEL: +31628248531

RESEARCH AREA

In my research I address communicative AI: AI that is open for inspection by humans and engages in communicative interfaces with humans. In particular, I focus on deep learning and natural language processing. It emphasizes the explainability and auditability of human-centered AI, and explicitly seeks connection with neurocognition, neuro/-psycholinguistics and general linguistics - disciplines that resort under LUCL. Further, the chair enforces the connection with LIACS (Leiden Institute of Advanced Computer Science) and the digital humanities community in Leiden (LUCDH, Leiden University Center for Digital Humanities) and the Netherlands. My professorship reflects TNO's orientation on trustworthy, transparent and controllable AI and will contribute to a better knowledge position for TNO on human-AI interaction.

RECENT RESULTS

I started in December 2019. Anticipating the start,  preparations have been carried out, including the installment of a new AI lab by me and Antal van den Bosch (director Meertens Institute and professor at Radboud University). This lab, co-founded with KNAW and CWI, will infuse the digital humanities data from KNAW (plus associated stakeholders such as Beeld en Geluid, Koninklijke Bibliotheek, and Rijksmuseum) into a community hub that targets the urgent problem of bias in AI. Natural language processing will be at the core of the lab. Stephan has been nominated as Distinguished Lorentz Fellow by Leiden University in October 2019. 

PHD SUPERVISION

• Not yet installed, but grant applications have been submitted (NWO, Perspectief, Defense (DO)).

TOP PUBLICATIONS

• Brewster, C., Nouwt, B., Raaijmakers, S., & Verhoosel, J. (n.d.). “Ontology-based access control for FAIR data”. Data Intelligence, 2(2020), 66–77.
• Stephan Raaijmakers. “Deep learning for natural language processing”. Manning publications,
• Raaijmakers, S., & Brewster, C. “Exploiting Ontologies for Deep Learning: A Case for Sentiment Mining”. In Proceedings of the 14th ACM International Conference on Semantic Systems, Posters and demo track, 2018.
• Raaijmakers, S., Sappelli, M., & Kraaij, W. “Investigating the interpretability of hidden layers in deep text mining”. In Proceedings of the 13th ACM International Conference on Semantic Systems, pp. 177-180, 2017.

LINKS

LinkedIn: https://nl.linkedin.com/stephanraaijmakers