Stefano Galvan
Papers
10
Total Citations
206
H-Index
7
About
Stefano Galvan is a leading researcher at the intersection of robotics, neuroscience, and minimally invasive surgery, with a primary focus on developing intelligent systems for keyhole neurosurgery. His most significant contributions lie in the creation of novel path-planning algorithms for steerable needles, including the Adaptive Hermite Fractal Tree (AHFT) and an inverse reinforcement learning framework, which enable safe, curvature-constrained navigation through delicate brain tissue. Galvan’s work on the modular robotic platform for precision neurosurgery, featuring a bio-inspired needle, has achieved first in-vivo deployment, marking a major translational milestone. He has also advanced targeted drug delivery in the brain, providing critical insights into infusion-based techniques for treating glioblastoma. His research, which has garnered over 200 citations, is complemented by pioneering work in brain deformation simulation using Position-Based Dynamics and early contributions to teleoperation architecture. Notably, Galvan’s innovative use of LEGO sets for robotics education demonstrates a commitment to inspiring the next generation of engineers. His multidisciplinary approach continues to push the boundaries of what is possible in robot-assisted neurosurgery.
Research Focus
Key Achievements
Top Papers
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- 4Innovative robotics teaching using LEGO sets27 citations · 2006
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- 7Advanced Teleoperation Architecture11 citations · 2006
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- 9Supervisory-Control Robots2 citations · 2020
- 10Advanced Teleoperation Architecture2 citations · 2007