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Subodh Bhujel is a rising researcher at the forefront of neurorehabilitation and human-robot interaction, specializing in the development of intelligent robotic systems for upper extremity recovery. His work critically compares rehabilitation robot architectures—such as end-effector versus exoskeleton types—providing essential guidance for designing more effective therapeutic devices. Bhujel has made significant contributions by integrating neural networks into robotic exoskeletons, enabling these systems to interpret complex physiological signals like sEMG, EMG, and EEG for adaptive, patient-specific therapy. His systematic review on this topic (2025, 18 citations) has become a key resource for researchers exploring AI-driven rehabilitation. With his most cited work, “A comparative study of end-effector and exoskeleton type rehabilitation robots” (2023, 28 citations), and his comprehensive analysis of emerging trends (2024, 17 citations), Bhujel has established himself as a leading voice in the field. His research directly addresses the pressing need for innovative neurorehabilitation solutions for stroke survivors and the elderly, bridging the gap between robotics, artificial intelligence, and clinical therapy.