Sugang Ma

Shandong Institute of Automation, Xi’an University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Sugang Ma’s research lies at the intersection of robotics, computer vision, and mobile security. A foundational contribution is his early work on **depth assessment using qualitative stereo-vision** (2002), which introduced a method for mobile robots to gauge distances to obstacles via stereo cameras mounted on a pan-tilt platform—a practical approach for autonomous navigation. This paper has garnered 4 citations, reflecting its niche but lasting influence on robotic perception. More recently, Ma has ventured into secure AI deployment with **EffTEE** (2025), a framework for efficient image classification and object detection on mobile devices using Trusted Execution Environments. Addressing critical security challenges in autonomous driving, UAV navigation, and robotics, this work has already attracted 1 citation, signaling growing interest in privacy-preserving DNN execution. By bridging classic robotics techniques with cutting-edge secure computing, Ma demonstrates a versatile research trajectory. His contributions highlight a commitment to both foundational algorithms and applied security, making his work relevant for students and researchers exploring safe, intelligent mobile systems.