Salar Basiri
Papers
4
Total Citations
87
H-Index
4
About
Salar Basiri is a researcher whose work bridges control theory, robotics, and human–machine interaction. His early contributions include pioneering the optimal design of LQR weighting matrices using intelligent optimization methods—a 2011 paper that has earned 41 citations and remains a key reference for engineers seeking to automate controller tuning. More recently, Basiri has focused on assistive robotics and accessibility, leading the design and implementation of a robotic architecture for adaptive teaching of Iranian Sign Language. Two of his 2021 papers, each with 20 citations, detail how optimized deep neural networks enable dynamic sign language recognition, demonstrating a practical, robotic-based system for communication support. His foundational work also includes the kinematic analysis of passive bipedal walking robots, where he used image processing to study motion on declined surfaces. Across these projects, Basiri shows a consistent interest in combining optimization algorithms with real-world robotic applications—from control systems to inclusive education technologies. His work stands out for its applied impact, particularly in making robotic systems more adaptive and accessible for diverse users.
Research Focus
Key Achievements
Top Papers
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