Glebys Gonzalez
Papers
10
Total Citations
194
H-Index
7
About
Glebys Gonzalez is a pioneering researcher at the intersection of robotic surgery, human factors, and autonomous systems. Her work focuses on making telesurgery viable in austere and remote environments where communication delays and bandwidth limitations pose critical challenges. Gonzalez’s major contributions include developing semi-autonomous frameworks like DESERTS and ASAP, which enable surgical robots to operate safely under high-latency conditions by transferring dexterous surgical skills between robots and procedures. She also advanced workload prediction in robot-assisted surgery, using multimodal physiological signals to objectively assess surgeon cognitive load—a breakthrough over subjective questionnaires. Her most cited paper, "Multimodal Physiological Signals for Workload Prediction in Robot-assisted Surgery," has garnered 58 citations, reflecting its impact on surgical training and system design. Gonzalez created the DESK dataset, a key resource for training machine learning models in dexterous surgical skill transfer, and her work has been recognized for its dual-use potential, from the operating room to the battlefield. Her research not only enhances surgical safety and efficiency but also paves the way for autonomous robotic assistance in critical care, making her a leading voice in the future of telemedicine and robotic autonomy.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3DESERTS: DElay-tolerant SEmi-autonomous Robot Teleoperation for Surgery25 citations · 2021
- 4
- 5
- 6
- 7SARTRES: a semi-autonomous robot teleoperation environment for surgery15 citations · 2020
- 8Joint Surgeon Attributes Estimation in Robot-Assisted Surgery5 citations · 2018
- 9
- 10