PHD Candidate, School of Aerospace Science and Technology, Xidian University, China 🌟
Xiaojun Li is a dedicated Ph.D. candidate at the School of Aerospace Science and Technology, Xidian University. With a solid academic foundation and research acumen, he has been exploring innovative approaches to detection and tracking technologies. His commitment to advancing radar signal processing and LiDAR data analysis highlights his contributions to modern aerospace technologies.
Profile
Orcid
Education 📚
Xiaojun Li completed his B.S. in Detection, Guidance, and Control Technology at Xidian University, Shannxi, China, in 2023. He is currently pursuing his Ph.D. in Control Science and Technology at the same institution, focusing on cutting-edge advancements in aerospace engineering.
Experience 🛠️
As a student researcher, Xiaojun has been actively involved in developing innovative solutions for low, small, and slow target detection. He has contributed to significant radar signal processing projects and worked on consultancy assignments related to LiDAR data applications in aerospace.
Research Interests 🔍
Xiaojun Li’s research focuses on advancing detection and tracking technologies, particularly for low, small, and slow targets. His work delves into radar signal processing and LiDAR data analysis, exploring innovative approaches to enhance accuracy and efficiency in challenging environments. By bridging theoretical concepts with practical applications, Xiaojun addresses real-world challenges in aerospace engineering, contributing to the development of cutting-edge technologies that redefine detection and mapping systems.
Awards 🏆
While primarily focused on academic and research pursuits, Xiaojun Li has been recognized for his contributions to radar signal and LiDAR data processing technologies. His achievements reflect his dedication to innovation in the field.
Publications Top Notes🖋️
Wang, W., Yan, B., Li, X., et al. (2024). “Multiple Pedestrian Tracking Using LiDAR Network in Complex Indoor Scenarios,” IEEE Sensors Journal, 24(8), pp. 13175–13192. DOI: 10.1109/JSEN.2024.3369947.
Cited by: 5 articles
Li, X., Hu, G., et al. (2024). “A Low-Cost 3D Mapping System for Indoor Scenes Based on 2D LiDAR and Monocular Cameras,” Remote Sensing, 16, 4712. DOI: 10.3390/rs16244712.
Cited by: 3 articles
Conclusion
Xiaojun Li is a promising candidate for the Best Researcher Award, with a solid foundation in innovative technologies and high-impact publications. Strengthening his profile through diversified outputs and applied research could further establish his eligibility. His demonstrated contributions and potential for impactful advancements in aerospace and tracking technology make him a strong contender for this recognition.