Zichao Geng

Beijing University of Chemical Technology

Papers

Total Citations

H-Index

About

Dr. Zichao Geng is a rising researcher in computer vision and robotics, whose work bridges deep learning with real-world autonomous systems. His primary research areas include pedestrian tracking, robotic grasping, and intelligent perception for autonomous driving and industrial automation. In his influential 2021 study on pedestrian tracking, Dr. Geng advanced the application of deep learning to enable robust tracking for complex tasks like human pose estimation and behavior analysis—critical for autonomous driving and intelligent security. His 2022 work introduced a novel real-time grasping method combining YOLO with a Grasp Detection Fully Convolutional Network (GDFCN), addressing the challenge of grasping complex targets for mobile robotic arms in industrial and transportation settings. Each of his most-cited papers has garnered 5 citations, reflecting growing recognition in the field. Dr. Geng’s contributions are particularly notable for their practical impact on emerging technologies, from service robotics to intelligent transportation, positioning him as a key innovator in making autonomous systems more perceptive and dexterous.