Natalia Sanchez‐Tamayo
Papers
6
Total Citations
84
H-Index
5
About
Natalia Sanchez‐Tamayo is a robotics researcher whose work sits at the intersection of surgical robotics, machine learning, and human-robot interaction. Her primary research focuses on enabling semi-autonomous teleoperation for surgical robots, particularly in austere and time-critical environments like battlefields or disaster zones where communication links may be unreliable. She made a major contribution with the creation of the DESK dataset—a robotic activity dataset for dexterous surgical skills transfer—which has become a foundational resource for training machine learning models in semi-autonomous surgery and skill assessment (29 citations). Her SARTRES system advances this vision by allowing robots to take over during communication delays, while her work on transferring dexterous skill knowledge between robots (18 citations) demonstrates how learned surgical motions can be adapted across different robotic platforms. Sanchez‐Tamayo also pioneered the adaptation of industrial collaborative robots like the ABB YuMi into affordable, open surgical research platforms, lowering barriers for education and prototyping. Her exploration of one-shot gesture recognition further pushes toward adaptive, intuitive human-robot interaction. With over 80 combined citations, her research is shaping the future of deployable, autonomous-capable surgical robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3SARTRES: a semi-autonomous robot teleoperation environment for surgery15 citations · 2020
- 4Collaborative Robots in Surgical Research11 citations · 2018
- 5One-Shot Gesture Recognition: One Step Towards Adaptive Learning8 citations · 2017
- 6