Mr. Yongnan Xu, Sichuan University, China
Mr. Yongnan Xu is a dedicated researcher and scholar at Sichuan University, where he focuses on multi-objective optimization, integrated space-air-ground networks, unmanned aerial vehicle (UAV) networks, and neural networks. He earned his B.S. degree from Shenzhen University and an M.S. degree in Electronic Information from Sichuan University. With three SCI papers, one conference paper, and two patents to his name, Mr. Xu has made significant contributions to the field, particularly in enhancing channel capacity fairness for ground devices in integrated networks and improving neural network efficiency through joint optimization techniques. His ongoing research projects include developing satellite internet support technology and high-temperature gas measurement technologies. Mr. Xu’s work is recognized internationally, and he is a nominee for the Best Researcher Award.
Professional Profile:
SCOPUS
Summary of Suitability for Best Researcher Award:
Mr. Yongnan Xu is a highly qualified candidate for the Best Researcher Award, recognized for his contributions to the field of electronic information and integrated networks. His academic achievements, innovative research projects, and practical applications position him as a leader in his domain.
Education 🎓
- B.S. in Engineering
Shenzhen University
- M.S. in Electronic Information
Sichuan University
Work Experience 💼
- Researcher
Sichuan University
Focus: Integrated space-air-ground networks and multi-objective optimization
Year: 2021 – Present
Achievements 🏆
- Publications:
- 3 SCI papers
- 1 conference paper
- Filed 2 patents
- Research Projects:
- Research on Satellite Internet Support Technology in Areas with Weak Communication Resources based on Low-orbit Constellation Satellites (2021YFQ0011, Sichuan Province)
- Research on High Temperature and High Pressure Gas Measurement Technology of Nuclear Reactor (Horizontal research project of Sichuan University)
- Citation Index:
All references cited 9 times
Patents 🛠️
- A Multi-Objective Optimization Method for Air-to-Earth Communication Resources based on Pareto Optimal Solution (CN 202311028249.9)
- Status: Passed the first reading (October 20, 2023)
- A Routing Scheme Combining Floyd Algorithm and Reinforcement Learning in LEO Satellite Networks (CN 202410130728.X)
- Status: Passed the first reading (January 31, 2024)
Awards and Honors 🌟
- Best Researcher Award (Nomination in Progress)
- Network of Conservation Educators and Professionals 2017
- Travel Award to attend Conservation Teaching and Learning Studio
- EPPS Outstanding Teaching Comet Award
Publication Top Notes:
A Multiarea On-Demand Classification Constellation Design for Satellite IoT
Multi-objective Resource Allocation across Multiple IoT Device Categories in Space-Air-Ground Integrated Network