Max Robotics — Global Service Robot Directory + US Certification

About

Dr. Yunji Liang is a leading researcher at the intersection of cybersecurity, artificial intelligence, and autonomous systems. His work spans two critical domains: behavioral biometrics for IoT security and robust 3D perception for autonomous driving. Dr. Liang’s most influential contribution, “Behavioral Biometrics for Continuous Authentication in the Internet-of-Things Era: An Artificial Intelligence Perspective” (2020), has garnered over 200 citations, establishing a foundational framework for using AI-driven behavioral patterns—such as touch dynamics and gait—to provide seamless, continuous user authentication in smart environments. This work addresses the limitations of traditional password and biometric systems in the IoT era. More recently, Dr. Liang has made significant strides in computer vision for autonomous driving. His paper “SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimation” (2024, 51 citations) introduces a novel self-supervised method that recovers fine-grained scene details from a single camera, a critical capability for safe navigation. He has also pioneered robust 3D multi-object tracking under adverse weather conditions, with works like “Cross-Modality 3D Multiobject Tracking Under Adverse Weather via Adaptive Hard Sample Mining” (2024), which tackles performance degradation caused by rain, fog, and snow. Through his research on hard sample mining and cross-modality fusion, Dr. Liang is advancing the reliability of autonomous systems in real-world, challenging environments.