Shi Long Song

Hong Kong University of Science and Technology

Papers

Total Citations

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About

Shi Long Song is a pioneering researcher at the intersection of assistive robotics and special education, with a primary focus on developing technology-mediated interventions for individuals with autism spectrum disorders (ASD). His most-cited work, "A Robot-Assisted Scenario Training for Students with ASD" (2024), addresses a critical challenge: helping students with ASD navigate unfamiliar environments by reducing social anxiety and building adaptive behaviors through structured, robot-guided scenarios. This contribution is notable for its practical, human-centered approach—using robots not as replacements for human interaction but as predictable, non-judgmental partners that scaffold learning. While still early in his career, Song’s research has already garnered attention (3 citations) for its innovative fusion of robotics, behavioral science, and inclusive education. His work stands out for its direct applicability in schools and therapy settings, offering a scalable tool to support students who often feel insecure due to social challenges and a lack of environmental support. Song’s ongoing efforts promise to reshape how technology can foster independence and confidence in neurodiverse learners.