Papers
25
Total Citations
1,290
H-Index
11
About
Fernando Bello is a multidisciplinary researcher whose work spans surgical robotics, soft robotics, haptics, and advanced robotic manipulation. His early and highly influential contributions focused on robotic-assisted surgery, particularly the da Vinci telemanipulator system, where he investigated dexterity enhancement, stereoscopic vision benefits, and the quantification of surgical skill acquisition — work that collectively garnered nearly 700 citations and helped establish evidence-based frameworks for evaluating robotic surgical training. His development of ROVIMAS, a dedicated software package for assessing surgical competency, further demonstrated his commitment to bridging technology and clinical education. Beyond surgery, Bello has made notable contributions to soft robotics, co-authoring a 2020 paper proposing a unified materials database for finite element modeling of soft-bodied robots, which has already accumulated over 325 citations. His research portfolio also encompasses teleoperation under uncertainty, machine learning for robotic manipulation, prosthetic hand rehabilitation through virtual reality, and innovative gripper design — exemplified by the Hydra Hand's switchable grasping modes. This breadth reflects a researcher driven by the challenge of making robots safer, smarter, and more responsive to human needs across clinical, industrial, and assistive contexts.
Research Focus
Key Achievements
Top Papers
- 1Toward a Common Framework and Database of Materials for Soft Robotics326 citations · 2020
- 2Dexterity enhancement with robotic surgery324 citations · 2004
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- 6Image guidance for robotic minimally invasive coronary artery bypass39 citations · 2009
- 7Machine learning meets advanced robotic manipulation35 citations · 2024
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