Papers
7
Total Citations
45
H-Index
4
About
Sergey A. Sheptunov is a pioneering researcher at the intersection of artificial intelligence, robotics, and medicine, with key contributions in robotic surgery, rehabilitation engineering, and AI-driven software reliability. His most cited work (14 citations) introduces a neural network-based model for simulating software reliability in robotic systems, demonstrating how AI can predict failure rates during debugging. In pediatric rehabilitation, Sheptunov’s 2017 study (12 citations) designed a robotic-assisted complex for children with cerebral palsy, addressing critical gaps in early motor function therapy. He has also advanced next-generation surgical robotics, evaluating the potential for mechatronic surgical complexes (9 citations), and explored the use of convolutional neural networks for machine learning in robotic surgery. A notable theoretical contribution is his neuron network model of human personality, proposed for integrating human-like decision-making into medical robotic systems. Sheptunov’s work bridges AI, robotics, and clinical application, with cumulative citations reflecting growing impact in rehabilitation and surgical automation. His research is essential for students and engineers developing intelligent, human-centered robotic systems for healthcare.
Research Focus
Key Achievements
Top Papers
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- 7SIMULATORS IN ROBOTIC SURGERY TRAINING (LITERATURE REVIEW)2 citations · 2016