Mr. Yongnan Xu | Internet of Things Awards | Best Researcher Award

Mr. Yongnan Xu | Internet of Things Awards | Best Researcher Award 

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:
    1. Research on Satellite Internet Support Technology in Areas with Weak Communication Resources based on Low-orbit Constellation Satellites (2021YFQ0011, Sichuan Province)
    2. 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 🛠️

  1. 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)
  2. 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
    • 2014, 2015, 2016

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

Mr Anandarup Roy | Internet of Things | Best Researcher Award

Mr Anandarup Roy| Internet of Things | Best Researcher Award

Mr Anandarup Roy,Senior Research Fellow, Indian Statistical Institute, Kolkata,India

Anandarup Roy is a Ph.D. candidate in Computer Science at the Indian Statistical Institute (ISI), Kolkata, specializing in combinatorial secret sharing. His thesis was submitted on July 19, 2024, and he expects to receive his degree by December 2024. He is advised by Prof. Bimal Kumar Roy and co-supervised by Prof. Mridul Nandi, both from the Applied Statistics Unit at ISI.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

Anandarup Roy, a Ph.D. candidate at the Indian Statistical Institute, has made significant contributions to the field of computer science, particularly in combinatorial secret sharing. His research extends previous work in Bayesian incentive-compatible mechanism design and social learning, demonstrating a robust understanding of complex statistical models and their applications.

Education

He Naifeng is pursuing a PhD at the prestigious Nanjing University of Aeronautics and Astronautics, where he has built a strong foundation in automation and robotics. His academic journey reflects a commitment to advancing technology in mobile robotics, demonstrating a keen interest in both theoretical knowledge and practical applications.

Work Experience

From 2016 to 2018, Anandarup worked as a project-linked person at the Economics Research Unit of ISI, where he contributed to a project on Bayesian incentive-compatible mechanism design under the supervision of Prof. Manipushpak Mitra. This research extended his master’s thesis by examining learning processes in a social choice environment with risk-neutral agents.

Skills

Anandarup is proficient in using Linux OS (Ubuntu) and LaTeX. He possesses basic programming knowledge in C, making him well-equipped for computational tasks related to his research.

Research Focus

His research focuses on autonomous navigation for wheel-legged robots, with particular emphasis on reinforcement learning in control systems and intelligent motion control. He aims to develop practical applications that enhance the performance and adaptability of mobile robots in challenging environments.

Publication top Notes:

  • Combining Dynamic Selection and Data Preprocessing for Imbalance Learning
    Year: 2018
    Journal: Neurocomputing
    Volume/Pages: 286, 179-192
  • SVM-based Hierarchical Architectures for Handwritten Bangla Character Recognition
    Year: 2009
    Journal: International Journal on Document Analysis and Recognition (IJDAR)
    Volume/Pages: 12, 97-108
  • Lecithin and Venom Haemolysis
    Year: 1945
    Journal: Nature
    Volume/Pages: 155 (3945), 696-697
  • A Novel Approach to Skew Detection and Character Segmentation for Handwritten Bangla Words
    Year: 2005
    Journal: Digital Image Computing: Techniques and Applications (DICTA’05)
    Pages: 30-30
  • JCLMM: A Finite Mixture Model for Clustering of Circular-Linear Data and Its Application to Psoriatic Plaque Segmentation
    Year: 2017
    Journal: Pattern Recognition
    Volume/Pages: 66, 160-173
  • An HMM Framework Based on Spherical-Linear Features for Online Cursive Handwriting Recognition
    Year: 2018
    Journal: Information Sciences
    Volume/Pages: 441, 133-151
  • Pair-Copula Based Mixture Models and Their Application in Clustering
    Year: 2014
    Journal: Pattern Recognition
    Volume/Pages: 47 (4), 1689-1697
  • Character Segmentation for Handwritten Bangla Words Using Artificial Neural Network
    Year: 2005
    Journal: Proceedings of the 1st IAPR TC3 NNLDAR
  • SWGMM: A Semi-Wrapped Gaussian Mixture Model for Clustering of Circular–Linear Data
    Year: 2016
    Journal: Pattern Analysis and Applications
    Volume/Pages: 19, 631-645
  • Headline Based Text Extraction from Outdoor Images
    Year: Not specified (conference paper)
    Journal: Pattern Recognition and Machine Intelligence: 4th International Conference