Shubham Shah
Papers
8
Total Citations
77
H-Index
6
About
Shubham Shah is a robotics and biomedical engineering researcher whose work sits at the intersection of robotic manipulator design and medical applications. His research primarily focuses on developing intelligent, precision-guided robotic systems for clinical procedures, particularly CT-guided biopsies and diagnostic interventions. Shah has made notable contributions to solving one of robotics' most persistent challenges — inverse kinematics — pioneering the application of deep artificial neural networks to deliver faster and more accurate solutions, work that has garnered 27 citations and represents his most influential contribution to the field. His broader research portfolio demonstrates a sustained commitment to translating robotic technology into medical practice. From his early preliminary designs of 7-DOF needle-positioning manipulators to optimizing spatial manipulator mechanisms for computed tomography-guided procedures, Shah has consistently pushed the boundaries of medical robotics with both theoretical rigor and experimental validation. His work on vibration analysis and image-processing-based deviation analysis further reflects his comprehensive, systems-level approach to robot design. With a cumulative body of work exceeding 75 citations, Shah's research offers valuable frameworks for researchers and clinicians seeking to improve precision, safety, and autonomy in minimally invasive medical procedures.
Research Focus
Key Achievements
Top Papers
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- 8Design of a Robotic Arm3 citations · 2019