Ruizhi Zuo
Papers
2
Total Citations
5
H-Index
1
About
Ruizhi Zuo is a rising researcher at the forefront of surgical robotics and biomedical optics, whose work is pioneering autonomous, intelligent systems for minimally invasive surgery. His primary research areas include deep learning for surgical sensing, optical coherence tomography (OCT), and advanced endoscopic imaging. Zuo’s major contribution is the development of a hybrid MLP-DC-CNN classifier that enables automatic, real-time tissue sensing for autonomous intestinal anastomosis—a critical step in gastrointestinal and urologic surgeries. This work, published in 2024, has already garnered 4 citations and represents a significant leap toward the clinical viability of autonomous surgical robots like the STAR system. Additionally, Zuo has advanced endoscopic imaging by proposing a deep-learning-based single-shot fringe projection profilometry (FPP) method, which overcomes the traditional speed limitations of FPP by requiring only a single image acquisition. This innovation, published in 2025, promises to enable high-speed, dynamic 3D measurements during endoscopy. Through these contributions, Zuo is not only improving surgical precision and efficiency but also laying the groundwork for the next generation of smart, autonomous surgical tools.
Research Focus
Key Achievements
Top Papers
- 1
- 2