Prof. Dr. Yinwei Li | Radar Remote Sensing | Best Researcher Award

Prof. Dr. Yinwei Li | Radar Remote Sensing | Best Researcher Award 

Prof. Dr. Yinwei Li, University of Shanghai for Science and Technology, China

Dr. Yinwei Li is a Professor at the University of Shanghai for Science and Technology, specializing in radar detection and terahertz imaging. He received his Ph.D. from the University of Chinese Academy of Sciences in 2014 and earned his Bachelor’s degree from the University of Electronic Science and Technology of China in 2009. Dr. Li began his career at the Shanghai Radio Equipment Research Institute, where he served as an Engineer and later as a Senior Engineer from 2014 to 2019. He joined the University of Shanghai for Science and Technology in 2019 as an Associate Professor and was promoted to Professor in 2024. Actively engaged in the academic community, Dr. Li has been a reviewer for prominent journals including IEEE TGRS, IEEE J-STARS, IEEE GRSL, and the IEEE Sensors Journal. He is a member of IEEE and the Chinese Institute of Electronics and serves as a communications review expert for the National Natural Science Foundation of China. His contributions continue to advance the frontiers of imaging and detection technologies.

Professional Profile:

ORCID

🏆 Summary of Suitability – Best Researcher Award

Prof. Yinwei Li is an exceptionally qualified candidate for the Best Researcher Award, with an outstanding academic and professional trajectory in advanced radar detection and terahertz imaging technologies. Holding a Ph.D. from the prestigious University of Chinese Academy of Sciences, Prof. Li has consistently demonstrated research excellence across both academic and industry settings.

🎓 Education Background

  • 📚 Bachelor’s Degree
    University of Electronic Science and Technology of China
    Sept 2005 – July 2009

  • 🎓 Ph.D. in Radar/Imaging Technologies
    University of Chinese Academy of Sciences
    Sept 2009 – July 2014

💼 Work Experience

  • 👨‍🏫 Professor
    University of Shanghai for Science and Technology
    July 2024 – Present

  • 👨‍🏫 Associate Professor
    University of Shanghai for Science and Technology
    April 2019 – June 2024

  • 🧑‍🔧 Senior Engineer
    Shanghai Radio Equipment Research Institute
    Aug 2017 – March 2019

  • 🧑‍💻 Engineer
    Shanghai Radio Equipment Research Institute
    Aug 2014 – July 2017

🏅 Achievements & Honors

  • 🛰️ Contributed significantly to radar detection and terahertz imaging technologies

  • 📝 Reviewer for prestigious journals like IEEE TGRS, IEEE J-STARS, GRSL, and Sensors Journal

  • 🧠 Expert Reviewer for the National Natural Science Foundation of China (2017–Present)

  • 🌐 IEEE Member since 2016

  • 🎖️ Member of the Chinese Institute of Electronics since 2015

Publication Top Notes:

A Novel Deep Unfolding Network for Multi-Band SAR Sparse Imaging and Autofocusing

A Hierarchical Feature Fusion and Attention Network for Automatic Ship Detection From SAR Images

A Two-Step Motion Compensation Method for Polar Format Images of Terahertz SAR Based on Echo Data

An Adaptive Nonlinear Phase Error Estimation and Compensation Method for Terahertz Radar Imaging System

A Novel 2-D Autofocusing Algorithm for Real Airborne Stripmap Terahertz Synthetic Aperture Radar Imaging

Generalized Persistent Polar Format Algorithm for Fast Imaging of Airborne Video SAR

A Novel Multistage Back Projection Fast Imaging Algorithm for Terahertz Video Synthetic Aperture Radar

 

Assoc Prof Dr. Puhong Duan | Remote sensing Award | Young Scientist Award

Assoc Prof Dr. Puhong Duan | Remote sensing Award | Young Scientist Award

Assoc Prof Dr. Puhong Duan, Hunan University, China

Puhong Duan is an accomplished researcher and academic currently serving as an Associate Professor at the College of Electrical and Information Engineering, Hunan University, in Changsha, China. With a Ph.D. in Pattern Recognition and Intelligent Systems from Hunan University, which he completed in October 2021, Puhong has established himself as a leading expert in the fields of hyperspectral image classification, multi-source data fusion, and object detection. His academic journey began with a Bachelor’s degree in Mathematics and Statistics from Suzhou University, followed by a Master’s degree in Mathematics from Hefei University of Technology. Puhong’s career at Hunan University has seen a steady progression, starting as an Assistant Researcher in 2021, advancing to Associate Researcher in January 2023, and finally being appointed as an Associate Professor in April 2024. His research contributions have significantly advanced the understanding and application of intelligent systems in image processing and data fusion, making him a prominent figure in his field.

Professional Profile:

ORCID

Summary of Suitability for the Research for Young Scientist Award:

Dr. Puhong Duan is an accomplished researcher in the field of pattern recognition, intelligent systems, and remote sensing, with a specific focus on hyperspectral image classification, multi-source data fusion, and object detection. His academic background, including a Ph.D. from Hunan University, and his rapid progression through research and academic positions at Hunan University, showcase his dedication and expertise.

🎓 Education:

  • Ph.D. in Pattern Recognition and Intelligent System
    Hunan University, Changsha, China (Sep. 2017 – Oct. 2021)
  • M.S. in Mathematics
    Hefei University of Technology, Hefei, China (Sep. 2014 – May 2017)
  • B.S. in Mathematics and Statistics
    Suzhou University, Suzhou, China (Sep. 2009 – Jul. 2014)

💼 Working Experience:

  • Associate Professor
    Hunan University, Changsha, China (Apr. 2024 – Present)
  • Associate Researcher
    Hunan University, Changsha, China (Jan. 2023 – Mar. 2024)
  • Assistant Researcher
    Hunan University, Changsha, China (Nov. 2021 – Dec. 2022)

🔬 Research Interests:

  • Hyperspectral Image Classification 🌈
  • Multi-Source Data Fusion 🔗
  • Object Detection 🔍

Puhong Duan is a dedicated scholar and innovator in the field of pattern recognition and intelligent systems, focusing on advanced techniques like hyperspectral image classification and multi-source data fusion. His work significantly contributes to the progress of object detection technologies, pushing the boundaries of what’s possible in modern image analysis.

Publication top Notes:

Channel-Layer-Oriented Lightweight Spectral-Spatial Network for Hyperspectral Image Classification

Click-Pixel Cognition Fusion Network With Balanced Cut for Interactive Image Segmentation

EUAVDet: An Efficient and Lightweight Object Detector for UAV Aerial Images with an Edge-Based Computing Platform

A Robust Infrared and Visible Image Registration Method for Dual-Sensor UAV System

Edge-Guided Hyperspectral Change Detection

Feature Consistency-Based Prototype Network for Open-Set Hyperspectral Image Classification

Feature-Band-Based Unsupervised Hyperspectral Underwater Target Detection Near the Coastline