Thomas Demeester

Ghent University, Ghent University Hospital

Papers

Total Citations

H-Index

About

Thomas Demeester is a leading researcher at the intersection of natural language processing, human-robot interaction, and AI-driven education. His work focuses on developing socially aware, multimodal dialogue systems that enable more natural and effective communication between humans and machines. A key contribution is his pioneering use of generative AI and social robots for adaptive second language tutoring, as demonstrated in his highly cited 2024 paper (12 citations), which addresses the critical shortage of language teachers by creating personalized, interactive learning experiences. Demeester also advances the field of visually grounded conversation, notably through his 2022 work (5 citations) that generates context-aware, situated conversation starters for human-robot dialogue—a crucial step toward making robots more perceptive and engaging social partners. His research is distinguished by its practical, data-driven approach to complex challenges in multimodal interaction, with clear applications in education and assistive technology. By bridging cutting-edge AI with real-world human needs, Demeester is shaping the future of how we learn and interact with intelligent systems.