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About

Ivan Wang‐Hei Ho is a leading researcher at the forefront of intelligent vehicle systems, autonomous navigation, and robotics perception. His work primarily focuses on enabling safe, real-time localization and environmental awareness for autonomous vehicles through advanced LiDAR-based Simultaneous Localization and Mapping (SLAM) and odometry. Ho’s major contributions include pioneering efficient data exchange in vehicular fog networks, where his 2019 paper on 3D road map data exchange (38 citations) demonstrated how intelligent vehicles and roadside infrastructure can collaboratively detect hidden obstacles, significantly extending perception range. He has also advanced LiDAR-SLAM performance with his 2022 work on Real-Time GICP, a direct method optimized for CPU environments, and developed innovative filtering techniques in Invariant-DLIO (2025), which improves LiDAR-inertial odometry accuracy through invariant Kalman filtering. His incremental approach in Inc-DLOM (2025) further addresses localization challenges in complex environments. With a growing citation impact and a focus on practical, computationally efficient solutions, Ho’s research directly supports the deployment of safer, more reliable autonomous systems, making him a notable contributor to the fields of intelligent vehicles and robotics navigation.