Papers
7
Total Citations
127
H-Index
6
About
Gao Tang is a pioneering researcher at the intersection of robotic microsurgery and data-driven control, with a primary focus on advancing ophthalmic surgical automation. His most impactful work centers on developing robotic systems for Deep Anterior Lamellar Keratoplasty (DALK), a challenging corneal transplant procedure. Tang's major contributions include the first integration of Optical Coherence Tomography (OCT) guidance with robotic needle insertion for DALK, achieving the precise 90% depth penetration required for the "big bubble" technique—a feat that significantly reduces patient morbidity compared to traditional transplants. His 2019 paper on OCT-guided robotic needle insertion (40 citations) and subsequent 2022 work on data-driven modelling for DALK (18 citations) have established foundational techniques in microsurgical robotics. Beyond surgery, Tang has made notable advances in control theory, including automatic tuning for data-driven Model Predictive Control (36 citations) and bilevel optimization for UAV time-optimal trajectories. His work on autonomous robotic micro-suturing using OCT calibration further demonstrates his commitment to pushing the boundaries of surgical automation. With over 127 total citations, Tang's research is shaping the future of precision medicine and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Automatic Tuning for Data-driven Model Predictive Control36 citations · 2021
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