Yingjia Gao

Papers

Total Citations

H-Index

About

Yingjia Gao is an emerging researcher in applied artificial intelligence and robotics, with a focus on intelligent systems for sports automation. Her most cited work, "Tennis Ball Collection Robot Based on MobileNet-SSD" (2021), demonstrates a novel integration of lightweight deep learning architectures with robotic platforms to address a practical challenge in sports—automating the tedious task of tennis ball retrieval. By leveraging MobileNet-SSD for real-time object detection, Gao’s system achieves efficient, low-latency performance suitable for deployment on resource-constrained robots. This contribution sits at the intersection of computer vision, embedded AI, and human-robot interaction, offering a scalable solution for sports training environments. With 4 citations to date, her work has sparked interest among researchers exploring AI-driven automation in athletics. Gao’s research underscores the growing trend of deploying accessible, cost-effective robotic assistants in everyday settings, and her approach to combining lightweight neural networks with mobile robotics provides a foundation for future innovations in autonomous sports equipment management. Her work is particularly relevant for students and engineers interested in practical AI applications that bridge the gap between cutting-edge algorithms and real-world usability.