Sarvin Ghiasi
Papers
1
Total Citations
2
H-Index
1
About
Sarvin Ghiasi is a researcher at the forefront of soft robotics and embedded sensing, with a focus on enabling safer, more intelligent intraluminal medical procedures. Their most-cited work, "WaveLeNet: Transfer Neural Calibration for Embedded Sensing in Soft Robots" (2023), introduces a pioneering neural calibration framework that overcomes a critical barrier in soft robotics: the integration of miniature force and shape sensors without compromising mechanical compliance. By leveraging transfer learning, Ghiasi’s method allows sensors to adapt to varying robot configurations and environments, dramatically improving the accuracy and reliability of real-time feedback—essential for delicate tasks like bronchoscopy and cardiovascular intervention. This contribution addresses a long-standing challenge in the field, where traditional rigid sensors fail to match the flexibility of soft robots. With 2 citations in a nascent area, Ghiasi’s work is already influencing the next generation of adaptive medical robots. Their research bridges machine learning and mechanical design, promising to enhance surgical precision and patient outcomes. As a rising voice in soft robotics, Ghiasi is shaping how robots sense and interact with the human body, paving the way for more autonomous and responsive clinical tools.
Research Focus
Key Achievements
Top Papers
- 1