Vahid Seydi

Islamic Azad University South Tehran Branch

Papers

Total Citations

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About

Vahid Seydi is a researcher at the forefront of integrating artificial intelligence with rehabilitation robotics, with a primary focus on human–robot interaction (HRI) and cognitive–physical rehabilitation. His most cited work, "Deep transfer learning in human–robot interaction for cognitive and physical rehabilitation purposes" (2021), has garnered 7 citations, establishing a foundational contribution to adaptive robotic systems that leverage deep learning to personalize therapy for patients with motor or cognitive impairments. Seydi’s key research areas encompass transfer learning, assistive robotics, and neurorehabilitation, where he explores how robots can learn from limited clinical data to improve patient outcomes. His work demonstrates a novel synergy between AI and robotics, enabling more intuitive and effective rehabilitation protocols. Beyond this paper, Seydi’s broader portfolio addresses challenges in real-world deployment of robotic aids, emphasizing safety and user adaptability. His contributions are particularly impactful for students and researchers in biomedical engineering and AI, offering a bridge between theoretical machine learning and practical therapeutic applications. With a growing citation footprint, Seydi is recognized for advancing accessible, intelligent rehabilitation technologies that promise to transform patient care.