Papers

11

Total Citations

190

H-Index

8

About

Muhammad Mubasher Saleem is a leading researcher in tactile sensing and force feedback technologies for robotic surgical systems, with a particular focus on multi-axis, high-sensitivity sensors. His work spans capacitive, inductive, magnetic, and piezoelectric sensing modalities, all aimed at replicating the human sense of touch in surgical robots. His most cited paper (49 citations) introduces a soft multi-axis magnetic tactile sensor designed to decouple normal, shear, and angular forces for force feedback in robotic surgery. He has also made significant contributions to human activity recognition using 2D skeleton data and supervised machine learning (41 citations), and to high-sensitivity capacitive tactile force sensors for robot-assisted surgery (30 citations). Saleem’s innovations include designs leveraging fringing electric fields, magnetorheological elastomers, and mode-localization in MEMS gyroscopes. His work consistently emphasizes low-cost, high-sensitivity, and fully decoupled force measurement—critical for safe and precise surgical robotics. With over 190 cumulative citations and multiple recent publications in top venues, Saleem is shaping the future of haptic feedback in minimally invasive and robot-assisted surgery.

Research Focus

Key Achievements

8
H-Index
11
Papers
190
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
A Soft Multi-Axis High Force Range Magnetic Tactile Sensor for Force Feedback in Robotic Surgical Systems
49 citations · 2022
📈 Most Prolific Year: 2025 (3 Papers)
🤝 Key Collaborators: 31
🏛 Institutions: National University of Sciences and Technology, National Court Reporters Association, National University of Ireland, Maynooth

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago