Hakim Guedjou

Institut Systèmes Intelligents et de Robotique

Papers

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About

Hakim Guedjou investigates the intersection of human-robot interaction and cognitive robotics, with a particular focus on how social and motor behaviors shape learning between humans and machines. His work centers on understanding autism through motor signatures, exploring how subtle movement patterns can be detected and analyzed during human-machine interaction—a contribution that bridges robotics with neurodevelopmental research. Guedjou’s most cited study, “Toward a motor signature in autism” (2018), has garnered 15 citations, reflecting its relevance in both assistive robotics and clinical diagnostics. He further examines how individual social traits influence robot learning, as shown in his 2017 work presented to an international audience, and develops posture recognition techniques for imitation learning in human-robot settings (2016). These studies collectively advance the design of adaptive robots capable of responding to human behavioral cues, with implications for therapy, education, and inclusive technology. Guedjou’s research stands out for its interdisciplinary approach, merging robotics, psychology, and machine learning to create more intuitive and socially aware systems.