Zheqi Zhu

Papers

Total Citations

H-Index

About

Zheqi Zhu is a researcher at the intersection of artificial intelligence and robotics, with a particular focus on applying deep learning to real-world automation challenges. His most cited work, "Tennis Ball Collection Robot Based on MobileNet-SSD" (2021), exemplifies his approach: combining lightweight neural network architectures with practical robotic systems to solve labor-intensive tasks. By integrating MobileNet-SSD—an efficient object detection model—into an autonomous robot, Zhu demonstrated how AI can streamline sports facility maintenance, reducing the physical burden on players and staff. This work, which has garnered 4 citations, showcases his ability to bridge computer vision and robotics for tangible applications. Zhu's contributions are especially relevant for students and researchers interested in embedded AI, edge computing, and human-robot interaction. His research highlights the growing trend of deploying intelligent systems in everyday environments, from sports arenas to industrial settings. As the field of AI-driven robotics continues to expand, Zhu's practical, application-oriented work serves as a valuable reference for those seeking to develop efficient, deployable solutions that enhance human productivity.