Xinran Zhong

University of California, Los Angeles, Wuhu Hit Robot Technology Research Institute

Papers

Total Citations

222

H-Index

About

Xinran Zhong is a leading researcher at the intersection of medical imaging and intelligent robotics, with a primary focus on AI-driven cancer diagnostics and automated infrastructure inspection. His most impactful contribution is the development of **FocalNet**, a deep learning architecture for joint prostate cancer detection and Gleason score prediction in multi-parametric MRI (mp-MRI). This work, cited over **215 times**, directly addresses the critical limitation of inter-reader variability in clinical prostate cancer diagnosis by moving beyond qualitative interpretation to quantitative, automated analysis. Beyond oncology, Zhong has pioneered a **cloud-edge-terminal-based robotic system** for autonomous airport runway inspection, demonstrating his versatility in deploying distributed AI architectures for real-world, safety-critical tasks. This system integrates cloud computing, edge processing, and robotic terminals to enable efficient, continuous pavement monitoring. By bridging the gap between advanced computational models and practical clinical and industrial applications, Zhong’s research is shaping the future of precision medicine and autonomous infrastructure management.