Sayed Ali Zendehbad holds a Ph.D. in Biomedical Engineering (Bioelectronics) and has completed two Postdoctoral Research Fellowships in Computational and Cognitive Neuroscience at the University of Mazandaran, Iran. His interdisciplinary expertise bridges biomedical engineering, computational neuroscience, and neurorehabilitation, with a focus on developing intelligent diagnostic and therapeutic systems for neurological disorders.

Over the past decade, Ali’s research has centered on advancing biological signal processing, computational modeling of brain–body interactions, and AI-driven neurorehabilitation frameworks. His notable contributions include the design of EEG- and EMG-based biofeedback systems for post-stroke motor recovery, the development of optimization algorithms for neural interface adaptation, and the engineering of secure tele-rehabilitation platforms for remote monitoring of cognitive and motor performance.

His scholarly work has been published in leading international journals, covering topics such as neurocomputational modeling, trustworthy medical artificial intelligence, and deep learning–based clinical decision support systems. Beyond research, he has demonstrated academic leadership through international collaborations, workshop chairing, and active participation in peer review for high-impact journals.

َAli’s overarching goal is to integrate computational intelligence with neuroscience to create next-generation assistive and diagnostic systems, ultimately aiming to enhance clinical precision and improve patients’ quality of life.