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About

Mojtaba Akbari is a pioneering researcher at the intersection of medical robotics and artificial intelligence, with key contributions in robotic ultrasound imaging and intelligent lower-limb assistive devices. His work addresses critical healthcare challenges, from pandemic safety to mobility impairments. Akbari’s most impactful paper, “Robotic Ultrasound Scanning With Real-Time Image-Based Force Adjustment” (41 citations), introduced a robot-assisted system that automatically scans tissue, reducing sonographer-patient contact during COVID-19—a timely solution for enabling physical distancing. He further advanced medical imaging with “Robot-assisted Breast Ultrasound Scanning Using Geometrical Analysis of the Seroma and Image Segmentation” (9 citations), which controls five degrees of freedom for precise breast scanning. In rehabilitation robotics, Akbari’s “Artificial‐Intelligence‐Powered Lower Limb Assistive Devices” (19 citations) explores AI-driven home care technologies, while his “Deep Reinforcement Learning based Personalized Locomotion Planning for Lower-Limb Exoskeletons” (9 citations) introduces intelligent central pattern generators for personalized walking trajectories. His “Uncertainty-aware safe adaptable motion planning” (8 citations) enhances exoskeleton safety using random forest regression. With over 80 total citations, Akbari’s work is notable for its practical impact on patient care and rehabilitation, earning recognition for integrating real-time AI with robotic systems to improve clinical outcomes and user comfort.