Gianni Borghesan

About

Gianni Borghesan is a robotics researcher whose work spans mechatronics, surgical robotics, and soft robotics — fields where precision engineering meets real-world clinical and physical challenges. He first established himself through foundational contributions to tendon-based actuation systems, developing comprehensive models, identification techniques, and control algorithms for robotic fingers and hands. His early papers on this subject (2009–2011) have collectively accumulated over 250 citations, reflecting their lasting influence on the design of lightweight, dexterous robotic devices. Borghesan's research has since expanded into minimally invasive surgical robotics, where he has addressed critical challenges including autonomous endoscope control, compliant catheter navigation, and haptic feedback in laparoscopic surgery — work with significant implications for patient safety and surgical efficiency. His 2022 contributions to deep-learning-based shape sensing and compliant motion control highlight a sophisticated integration of machine learning with physical robot systems. More recently, his foray into 3D-printed soft magnetic microrobots (2023, 78 citations) demonstrates a bold pivot toward programmable small-scale robotics. Across his career, Borghesan consistently bridges theoretical rigor with practical medical and engineering impact, making his body of work essential reading for researchers in surgical and soft robotics alike.

Research Focus

Key Achievements

Top Papers

1. 1
   Modeling, Identification, and Control of Tendon-Based Actuation Systems

   178 citations · 2011
2. 2
   3D Printing of Small‐Scale Soft Robots with Programmable Magnetization

   78 citations · 2023
3. 3
   Integrated Mechatronic Design for a New Generation of Robotic Hands

   53 citations · 2009
4. 4
   Robotic Endoscope Control Via Autonomous Instrument Tracking

   49 citations · 2022
5. 5
   Tendon-based transmission systems for robotic devices: Models and control algorithms

   47 citations · 2009
6. 6
   Shape Sensing of Flexible Robots Based on Deep Learning

   45 citations · 2022
7. 7
   Combined OCT distance and FBG force sensing cannulation needle for retinal vein cannulation: in vivo animal validation

   41 citations · 2018
8. 8
   Deep-Learning-Based Compliant Motion Control of a Pneumatically-Driven Robotic Catheter

   40 citations · 2022
9. 9
   Design of tendon-driven robotic fingers: Modeling and control issues

   36 citations · 2010
10. 10
    Evaluation of Haptic Feedback on Bimanually Teleoperated Laparoscopy for Endometriosis Surgery

    32 citations · 2018

Key Collaborators

Contact & Links