Ivan Bejic
Papers
1
Total Citations
5
H-Index
1
About
Ivan Bejic is a researcher at the intersection of robotics, child development, and clinical diagnostics, with a primary focus on leveraging robotic technologies to improve autism spectrum disorder assessment. His most-cited work, "Classification of Child Vocal Behavior for a Robot-Assisted Autism Diagnostic Protocol" (2018), has garnered 5 citations and represents a pioneering effort to integrate machine learning and human-robot interaction into standard diagnostic procedures. Bejic’s key contribution lies in developing automated classification systems that analyze children’s vocal behaviors during robot-assisted sessions, aiming to enhance the speed, objectivity, and reliability of autism diagnosis—a critical need given the rising prevalence of the disorder and the severe social and economic burdens it imposes. By bridging robotics, behavioral analysis, and clinical practice, his work opens new pathways for early, scalable intervention tools. Though early in his career, Bejic’s research signals a promising shift toward data-driven, technology-enhanced diagnostic protocols that could transform how clinicians assess neurodevelopmental conditions, making assessments more accessible and consistent for affected families worldwide.
Research Focus
Key Achievements
Top Papers
- 1