Max Robotics — Global Service Robot Directory + US Certification

About

Peili Ma is a researcher whose work sits at the intersection of computer vision, deep learning, and intelligent robotic systems, with a particular focus on infrastructure inspection and automation. Ma's most significant contribution to the field is a lightweight encoder–decoder neural network for automatic pavement crack detection, published in 2023 and already amassing an impressive 144 citations — a testament to its practical value and methodological elegance. This work addresses a longstanding challenge in pavement assessment: reliably identifying small or subtle cracks against complex, noisy backgrounds, with both speed and accuracy. Complementing this, Ma developed a mobile robot-based road crack acquisition and analysis system that integrates virtual reality technology for remote image collection, streamlining the entire data-gathering pipeline. Beyond pavement diagnostics, Ma has explored broader applications of robotics and mixed reality, including an industrial robot training platform leveraging VR and mixed reality technologies, as well as research into pipeline leak detection and remote repair under hazardous operating conditions. Taken together, Ma's body of work reflects a consistent drive to bring intelligent automation and deep learning to real-world infrastructure challenges, making critical maintenance tasks safer, faster, and more reliable.