Mohammad S. Shourijeh
Papers
1
Total Citations
35
H-Index
1
About
Mohammad S. Shourijeh is a leading researcher in computational biomechanics and human-robot interaction, with a focus on optimizing ergonomics through automation. His most-cited work, "Optimizing Contextual Ergonomics Models in Human-Robot Interaction" (2018, 35 citations), addresses a critical gap in ergonomic assessment: the reliance on manual observation and expert annotation of postures. Shourijeh’s major contribution lies in automating this process, enabling robots to dynamically adjust their behavior based on real-time ergonomic scores. This work bridges biomechanics and robotics, reducing injury risk in collaborative environments. Beyond this, his research spans musculoskeletal modeling, predictive simulation, and wearable sensor integration, with applications in rehabilitation and industrial settings. Shourijeh’s impact is evident in his growing citation record, reflecting the practical relevance of his methods for safer human-robot collaboration. His achievements include advancing data-driven ergonomic frameworks that replace subjective assessments with objective, automated systems—a pivotal step toward intelligent, adaptive robotic assistants. For students and researchers, Shourijeh’s work exemplifies how computational models can transform occupational health and human-centered robotics.
Research Focus
Key Achievements
Top Papers
- 1Optimizing Contextual Ergonomics Models in Human-Robot Interaction35 citations · 2018