Yubin Fang

Shenzhen University, Shanghai University

Papers

Total Citations

H-Index

About

Yubin Fang is a researcher whose work bridges the fields of underwater computer vision and smart structural control. In underwater robotics, Fang introduced a novel multi-scale feature map fusion encoding method for object segmentation, achieving 7 citations since 2024 and advancing the reliability of autonomous systems in challenging marine environments. His earlier, highly interdisciplinary research focused on active vibration control of smart flexible beams with tip masses, where he developed a hybrid filtered-X variable step-size least mean square (FX-VSSLMS) algorithm. This work, which has garnered 6 citations, demonstrated significant improvements in suppressing structural vibrations by combining adaptive feedforward and feedback control strategies. Fang’s contributions are notable for their dual impact: enhancing both the perceptual capabilities of underwater robots and the precision of smart material systems. His ability to apply advanced signal processing and control theory across distinct domains—from deep-sea imaging to piezoelectric beam stabilization—showcases a versatile engineering mindset. For students and researchers, Fang’s work exemplifies how adaptive algorithms can solve real-world challenges in both autonomous systems and structural dynamics.