Shafagh Keyvanian
Papers
2
Total Citations
9
H-Index
2
About
Shafagh Keyvanian is a rising researcher at the intersection of human-robot interaction, biomechanics, and assistive robotics. Her work focuses on enabling fluid, intuitive collaboration between humans and robots, with a particular emphasis on physical co-manipulation and rehabilitation. Keyvanian’s major contributions include developing a **constraint-aware intent estimation framework** for dynamic human-robot object co-manipulation, which allows robots to infer human motion goals in real-time—a critical step toward seamless physical teamwork. Her 2024 paper on this topic has already garnered **7 citations**, signaling its early impact in the field. Additionally, she has advanced **realistic kinematic modeling** by learning joint space boundaries for both healthy and impaired human arms, addressing a key challenge in rehabilitation robotics and biomechanics. This work, published in 2023, lays the foundation for more accurate range-of-motion analysis and personalized robot-assisted therapy. By bridging online estimation with anatomical fidelity, Keyvanian’s research promises to make human-robot collaboration safer, more adaptive, and more responsive to individual user needs—a vital contribution as robots move from factories into homes and clinics.
Research Focus
Key Achievements
Top Papers
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