Mehrdad Boroushaki
Papers
4
Total Citations
43
H-Index
4
About
Mehrdad Boroushaki is a pioneering researcher in intelligent robotic systems, with a focus on swarm robotics, medical robotics, and assistive technologies. His work bridges artificial intelligence and mechanical control, notably developing an optimized deep neural network for dynamic Iranian Sign Language recognition—a system implemented via a robotic architecture that has garnered 20 citations for its innovative approach to human-robot interaction. Boroushaki’s early contributions include advancing robotic swarm coordination through particle swarm optimization (PSO), where he determined agent velocity to maximize flocking efficiency—a foundational study with 10 citations. In medical robotics, he designed an emotional learning controller for force control of laparoscopic instruments, addressing critical challenges in surgical precision (8 citations). More recently, he developed an intelligent assistive exo-glove that combines fuzzy logic and emotional learning to enhance finger strength for users with motor impairments, achieving 5 citations. Boroushaki’s work stands out for integrating cognitive-inspired control systems—such as emotional learning—into practical robotic applications, from surgery to rehabilitation. His research demonstrates a consistent commitment to creating adaptive, intelligent machines that improve human capabilities, making significant strides in both theoretical swarm dynamics and tangible assistive devices.
Research Focus
Key Achievements
Top Papers
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