Zhengjin Shi

Shenyang Ligong University, Shenyang University of Technology

Papers

Total Citations

H-Index

About

Zhengjin Shi is a researcher at the forefront of medical imaging and robotics, with key contributions spanning 3D reconstruction and intelligent motion control. His most notable work introduces X-CTCANet, a groundbreaking deep learning framework that reconstructs 3D spinal CT images directly from 2D X-ray data—a significant advancement that could reduce radiation exposure and imaging costs in clinical settings. This 2024 publication has already garnered 5 citations, signaling growing recognition in the biomedical imaging community. In robotics, Shi designed a cascaded model predictive controller for modular robot joints, addressing critical challenges in next-generation robotic systems. His 2022 paper on this topic (3 citations) demonstrates how servo control and model predictive principles can enhance the motion and power performance of modular joints, directly impacting overall robot body control. By bridging medical imaging and advanced robotics, Shi’s work exemplifies interdisciplinary innovation, offering practical solutions for safer diagnostics and more precise robotic actuation. His research continues to inspire students and engineers seeking to push the boundaries of AI-driven healthcare and autonomous systems.