Marzie Khalili
Papers
1
Total Citations
6
H-Index
1
About
Marzie Khalili is a researcher at the forefront of assistive robotics, specializing in the integration of computer vision and deep learning for the control of lower-limb exoskeletons. Her work addresses a critical challenge: enabling robotic devices to intelligently perceive and adapt to diverse real-world environments, thereby improving mobility for individuals with movement disabilities. Khalili’s most-cited paper, “Environment Recognition for Controlling Lower-Limb Exoskeletons, by Computer Vision and Deep Learning Algorithm” (2022), has garnered 6 citations, reflecting its foundational role in advancing context-aware exoskeleton control systems. By leveraging deep learning algorithms for environment recognition, her research bridges the gap between robotic hardware and adaptive, human-centric control—a key step toward safer and more intuitive assistive devices. Khalili’s contributions are particularly notable for their practical impact, offering a pathway to more autonomous and responsive exoskeletons that can navigate stairs, slopes, and uneven terrain. Her work stands as a promising contribution to the fields of rehabilitation engineering and human-robot interaction, with implications for improving quality of life for millions worldwide.
Research Focus
Key Achievements
Top Papers
- 1