Maher Abujelala
Papers
8
Total Citations
140
H-Index
6
About
Maher Abujelala is a researcher at the intersection of human-robot interaction, socially assistive robotics, and rehabilitation engineering, whose work has made meaningful contributions to how intelligent systems can adapt to and support human needs. His most influential contribution, "Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive Training" (2018), has garnered 79 citations and established him as a notable voice in personalized SAR systems that tailor interactions to individual user abilities. Beyond social robotics, Abujelala has advanced the field of motor rehabilitation technology, developing vision-based kinematic models such as MAGNI Dynamics for upper-limb robotic rehabilitation and exploring muscle fatigue as an adaptive trigger in therapy sessions. His survey on assistive technologies for multiple sclerosis management reflects a commitment to evidence-based, patient-centered innovation. Abujelala has also addressed the evolving landscape of human-robot collaboration in vocational and manufacturing environments, designing frameworks that help workers develop skills alongside increasingly automated systems. Collectively, his research spans clinical rehabilitation, adaptive machine learning, and workforce readiness — positioning him as a versatile contributor to the broader goal of making robotics more responsive, inclusive, and practically beneficial to human users.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Robot-aided rehabilitation using force analysis7 citations · 2015
- 6
- 7Adaptive robotic rehabilitation using muscle fatigue as a trigger6 citations · 2019
- 8v-CAT3 citations · 2018