Faisal Aljaber

Queen Mary University of London

Papers

6

Total Citations

62

H-Index

5

About

Faisal Aljaber is a leading researcher in soft robotics, with a focus on advancing sensorisation and control for medical and industrial applications. His work centers on developing proprioceptive and exteroceptive sensing systems for soft actuators, particularly for use in robot-assisted minimally invasive surgery (MIS) and fabric-based grippers. Aljaber’s major contributions include the introduction of abraded optical fibre bending sensors that are insensitive to pressure, enabling accurate shape sensing without external interference. He also pioneered multi-point waveguide sensors for inflatable fingers, allowing simultaneous detection of bending and external forces. His most cited paper, “Fusing Dexterity and Perception for Soft Robot-Assisted Minimally Invasive Surgery” (30 citations), summarizes key lessons from the STIFF-FLOP project, highlighting how soft robots can combine compliance with precise control. Aljaber has also developed eversion-capable fabric grippers with novel retraction mechanisms, pushing the boundaries of lightweight, collapsible manipulators. With over 60 total citations across his publications, his work is instrumental in bridging the gap between soft material compliance and reliable sensing—a critical step toward safer, more intuitive human-robot interaction in surgery and beyond.

Research Focus

Key Achievements

5
H-Index
6
Papers
62
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Fusing Dexterity and Perception for Soft Robot-Assisted Minimally Invasive Surgery: What We Learnt from STIFF-FLOP
30 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Queen Mary University of London

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago