Karel Van den Bosch
Papers
6
Total Citations
99
H-Index
4
About
Karel Van den Bosch is a researcher whose work sits at the intersection of human-robot interaction, artificial intelligence, and collaborative teaming. His research centers on the emerging field of **human-AI and human-robot co-learning** — the process by which humans and intelligent systems mutually adapt to one another over time to build effective collaborative relationships. His most cited work, "Design Patterns for Human-AI Co-Learning" (2022, 49 citations), established foundational frameworks for structuring this adaptive learning process, using innovative Wizard-of-Oz methodologies in demanding urban search-and-rescue scenarios. Alongside this, his 2021 paper on mutual adaptation in human-robot teams (30 citations) introduced a conceptual model of co-learning comprising iterative cycles of co-adaptation and communication, providing a rigorous theoretical backbone for the field. Van den Bosch extends his expertise beyond laboratory settings into high-stakes domains, as evidenced by his work on meaningful human control in military human-machine teaming. His contributions span conceptual modeling, empirical evaluation, and design methodology, making him a distinctive voice bridging cognitive science, robotics, and responsible AI. His growing citation record reflects increasing recognition of the critical importance of designing AI systems that genuinely learn *with* humans, rather than merely alongside them.
Research Focus
Key Achievements
Top Papers
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- 4Human-Robot Co-Learning for Fluent Collaborations6 citations · 2021
- 5Designing for Meaningful Human Control in Military Human-Machine Teams4 citations · 2023
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