Ghufran Shafiq
Papers
1
Total Citations
11
H-Index
1
About
Ghufran Shafiq is a researcher whose work sits at the critical intersection of robotics, control systems, and biomedical engineering. His primary research focuses on enhancing the precision of surgical robotics, particularly through the real-time estimation and cancellation of physiological tremor—the involuntary, rhythmic oscillation that limits the dexterity of hand-held surgical tools. Shafiq’s most cited work, “Online LS-SVM based multi-step prediction of physiological tremor for surgical robotics” (2013, 11 citations), addresses a fundamental bottleneck in microsurgery: the phase delay introduced by both hardware sensors and software filtering. By developing an online least-squares support vector machine (LS-SVM) model for multi-step prediction, his research enables proactive tremor compensation rather than reactive filtering, significantly improving cancellation accuracy. This contribution is vital for advancing robot-assisted surgery, where even micron-level errors can be consequential. Though his citation count is modest, the targeted impact of his work on real-time control algorithms for medical robotics is notable, laying groundwork for more responsive and reliable surgical systems.
Research Focus
Key Achievements
Top Papers
- 1