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About

Mohammad Wasil is a researcher whose work sits at the intersection of human-robot interaction, machine learning, and assistive technology, with a particular focus on robot-assisted therapy for individuals with Autism Spectrum Disorder (ASD). His research addresses one of the most pressing challenges in therapeutic robotics: reducing therapist workload by enabling robots to operate more autonomously during sessions, rather than relying on manual control protocols such as Wizard-of-Oz setups. Wasil's most significant contributions center on personalized behavior modeling — developing learning-based systems that allow robots to adapt their responses to individual users over time. His 2024 paper on learning-based personalization (7 citations) represents a notable advance in this direction, demonstrating how robots can be trained to tailor their behavior without constant human intervention. His 2022 survey on personalized behavior models (4 citations) provides a comprehensive foundation for the field, mapping the landscape of approaches applicable to autism therapy contexts. Earlier work in fuzzy logic-based robot control highlights his broad grounding in robotics fundamentals. Though still building his citation profile, Wasil's focused contributions to autonomous, adaptive therapeutic robots position him as an emerging voice in socially assistive robotics research.