Ruben Janssens
Papers
7
Total Citations
33
H-Index
4
About
Ruben Janssens is a rising researcher at the intersection of social robotics, artificial intelligence, and second language acquisition. His work focuses on enabling more natural, adaptive human-robot interaction through multimodal AI, with a particular emphasis on using social robots as personalized language tutors. His most cited paper, “Adaptive Second Language Tutoring Using Generative AI and a Social Robot” (2024, 12 citations), demonstrates how generative AI can power individualized conversational practice—addressing critical gaps in language education caused by teacher shortages. Janssens has also pioneered methods for generating visually grounded conversation starters from environmental context, and his research on predicting user errors, enjoyment, and engagement from multimodal temporal data pushes toward robots that can read social signals in real time. His investigations into child speech recognition and the limitations of audiovisual speech on robots reveal a careful, empirical approach to understanding where current systems fall short. With recent work on online prediction of user enjoyment using LLMs and multi-modal language models for embodied interaction, Janssens is helping shape a future where robots are not just conversational, but genuinely responsive social partners.
Research Focus
Key Achievements
Top Papers
- 1Adaptive Second Language Tutoring Using Generative AI and a Social Robot12 citations · 2024
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- 5Child Speech Recognition in Human-Robot Interaction: Problem Solved?3 citations · 2025
- 6Online Prediction of User Enjoyment in Human-Robot Dialogue with LLMs3 citations · 2025
- 7Multi-modal Language Models for Human-Robot Interaction2 citations · 2024