Blacksburg, VA, United States of America

Xiaolong Li


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations in Autonomous Driving by Xiaolong Li

Introduction

Xiaolong Li is an accomplished inventor based in Blacksburg, VA (US). He has made significant contributions to the field of autonomous driving through his innovative patent. His work focuses on enhancing the capabilities of motion prediction systems, which are crucial for the development of safe and efficient autonomous vehicles.

Latest Patents

Xiaolong Li holds a patent titled "System and method for motion prediction in autonomous driving." This patent presents a system that utilizes a deep-neural-network-based approach to perform perception and motion prediction from 3D point clouds. The system is designed to process a pair of LiDAR sweeps, providing classifications for each point in the second sweep and motion vectors that indicate the point's movement within the world coordinate system. The inclusion of a spatiotemporal pyramid network allows for the extraction of deep spatial and temporal features in a hierarchical manner. The training process is enhanced with spatial and temporal consistency losses, resulting in an improved motion planner for autonomous driving applications. Xiaolong Li has 1 patent to his name.

Career Highlights

Xiaolong Li is currently employed at Mitsubishi Electric Research Laboratories, Inc. His role involves advancing technologies that contribute to the future of autonomous driving. His expertise in deep learning and motion prediction has positioned him as a key player in the research and development of intelligent transportation systems.

Collaborations

Xiaolong Li has collaborated with notable colleagues, including Alan Sullivan and Siheng Chen. These partnerships have fostered a collaborative environment that encourages innovation and the sharing of ideas in the field of autonomous driving.

Conclusion

Xiaolong Li's contributions to motion prediction in autonomous driving exemplify the importance of innovation in this rapidly evolving field. His work not only enhances the capabilities of autonomous vehicles but also paves the way for safer and more efficient transportation solutions.

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