Sayed Ali Zendehbad, PhD, is a Postdoctoral Research Fellow specializing in cognitive neuroscience and biomedical engineering. His research focuses on the intersection of computational neuroscience, rehabilitation, and biomedical signal processing, with a primary emphasis on developing intelligent diagnostic systems for the objective assessment of neurological fatigue and neurorehabilitation.

His ten-year research journey has been dedicated to pioneering new neural rehabilitation technologies. His notable work includes designing electrophysiology-based biofeedback systems for post-stroke motor recovery, developing optimization algorithms for neural interfaces, and engineering secure tele-rehabilitation frameworks for remote monitoring of cognitive function. His scholarly contributions are published in high-impact journals covering computational modeling of biological systems, advanced neurorehabilitation protocols, trustworthy remote artificial intelligence (AI), and clinical decision-support systems powered by deep learning.

Aside from his primary research, he has demonstrated notable academic leadership by promoting international collaborations, chairing sessions at major workshops, and participating in peer review as both a journal reviewer and an exclusive manager. His overall research aim is to integrate advances in computational intelligence and neurobiology to develop next-generation solutions for neurological care, with the goal of improving clinical outcomes and enhancing human quality of life.