Dr. Hao Cui | Remote sensing | Best Researcher Award

Dr. Hao Cui | Remote sensing | Best Researcher Award

Dr. Hao Cui, Wuhan University, China

Hao Cui is a postdoctoral researcher at the State Key Laboratory of Geospatial Information Science at Wuhan University, specializing in the intelligent interpretation of remote sensing imagery. Since July 2021, he has been working under the mentorship of Professor Li Deren, building on his previous academic experiences. Hao earned his Ph.D. in Photogrammetry and Remote Sensing from Wuhan University, where he studied under Professor Zhang Guo from September 2018 to July 2021. His academic journey also includes a master’s degree obtained through a joint training program at the China Academy of Surveying and Mapping, as well as studies in Cartography and Geographic Information Systems at Lanzhou Jiaotong University. He holds a bachelor’s degree in Measurement and Control Engineering from Datong University of Science and Technology. Hao has hosted several prestigious projects, including the National Natural Science Foundation of China Youth Project and the China Postdoctoral Innovation Talents Support Plan Project. He has made significant contributions to his field, authoring or co-authoring 13 published papers, with 10 featured in top-tier journals, including ISPRS and TGRS.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Researcher Award: Hao Cui

Hao Cui is a highly qualified candidate for the Best Researcher Award, demonstrating exceptional expertise and a strong research background in remote sensing and image interpretation. His research direction focuses on the mechanisms and interpretation theory methods of remote sensing images applied in engineering, which aligns well with contemporary advancements in geospatial sciences.

🎓 Education

  • Postdoctoral Researcher
    State Key Laboratory of Geospatial Information Science, Wuhan University
    Intelligent Interpretation of Remote Sensing Imagery
    Advisor: Li Deren
    Duration: July 2021 – Present
  • Ph.D. Student
    State Key Laboratory of Geospatial Information Science, Wuhan University
    Photogrammetry and Remote Sensing
    Advisor: Zhang Guo
    Duration: September 2018 – July 2021
  • Master’s Joint Training
    China Academy of Surveying and Mapping
    Cartography and Geographic Information Systems
    Advisor: Zhang Li
    Duration: August 2016 – June 2018
  • Master’s Student
    School of Surveying and Geographic Information, Lanzhou Jiaotong University
    Cartography and Geographic Information Systems
    Advisor: Zhang Li
    Duration: September 2015 – July 2016
  • Bachelor’s Student
    Datong University of Science and Technology
    Measurement and Control Engineering
    Major: Surveying and Mapping Engineering
    Advisor: Han Liang
    Duration: September 2011 – July 2015

💼 Work Experience

  • Postdoctoral Researcher
    State Key Laboratory of Geospatial Information Science, Wuhan University
    Focus: Intelligent Interpretation of Remote Sensing Imagery
    Duration: July 2021 – Present

🏆 Awards and Honors

  • National Natural Science Foundation of China (Youth Project)
  • China Postdoctoral Innovation Talents Support Plan Project
  • China Postdoctoral Excellent Young Talents Project
  • China Association for Science and Technology Think Tank Young Talent Plan Project
  • East Asian Satellite Remote Sensing Application Key Laboratory of Natural Resources Ministry of China Fund Project

Publication Top Notes:

Rice recognition from Sentinel-1 SLC SAR data based on progressive feature screening and fusion

SparseFormer: A Credible Dual-CNN Expert Guided Transformer for Remote Sensing Image Segmentation with Sparse Point Annotation

Assoc. Prof. Dr. Jie Zhao | Remote Sensing Awards | Best Researcher Award

Assoc. Prof. Dr. Jie Zhao | Remote Sensing Awards | Best Researcher Award

Assoc. Prof. Dr. Jie Zhao, Beijing University of Technology, China

  Dr. Jie Zhao is an Associate Professor at the School of Physics and Optoelectronic Engineering at Beijing University of Technology, China. She earned his Ph.D. in Optics from the university, where she also completed her Master’s degree. Dr. Zhao gained international research experience as a joint-cultured Ph.D. student at the University of Sheffield, UK. Her primary research interests include optical information processing, digital holographic microscopy, and Fourier ptychography imaging, with a focus on biological samples and terahertz wave phase-contrast imaging.She has contributed significantly to the advancement of diffraction tomographic imaging and continuous terahertz holography. Dr. Zhao has published numerous peer-reviewed articles in prominent journals and holds multiple patents.She is also an active member of the Society of Photo-Optical Instrumentation Engineers (SPIE) and has served as a postdoctoral researcher at the Henan Institute of Metrology.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Researcher Award – Jie Zhao

Dr. Jie Zhao is an Associate Professor at Beijing University of Technology (BJUT), specializing in Optics and Optoelectronics. With a strong background in terahertz imaging, computational tomography, and optical information processing, Dr. Zhao has made significant contributions to both theoretical and applied optics. His extensive research output and collaborative efforts position him as an excellent candidate for the Best Researcher Award.

Education:

  • Sep. 2007 – July 2011: Ph.D. in Optics, College of Applied Sciences, Beijing University of Technology (BJUT), China.
    • Joint-cultured Ph.D. student at the College of Electronic and Electrical Engineering, The University of Sheffield, UK (Sep. 2008 – Sep. 2009).
  • Sep. 2005 – July 2007: Master’s in Optics, College of Applied Sciences, BJUT, China.
  • Sep. 2001 – July 2005: Bachelor’s in Science and Technology of Optical Information, College of Physics Science & Technology, Hebei University, China.

Professional Experience:

  • Aug. 2011 – Present: Associate Professor/Lecturer, School of Physics and Optoelectronic Engineering, BJUT, China.
    • Courses taught: Optics, College Physics, and Optical Information Processing.
  • Nov. 2017 – Nov. 2020: Postdoctoral Researcher, Henan Institute of Metrology, China.
  • Sep. 2011 – Present: Member of SPIE (International Society for Optics and Photonics).

Publication top Notes:

Continuous-wave terahertz in-line holographic diffraction tomography with the scattering fields reconstructed by a physics-enhanced deep neural network

High accuracy terahertz computed tomography using a 3D printed super-oscillatory lens

Binary diffractive lens with subwavelength focusing for terahertz imaging

Binocular full-color holographic three-dimensional near eye display using a single SLM

Diffraction tomography based on Fourier ptychographic microscopy with the multiple scattering model

Continuous-Wave Terahertz In-Line Digital Holography Based on Physics-Enhanced Deep Neural Network

Ms. Oumayma Sadgui | Remote Sensing Awards | Women Researcher Award

Ms. Oumayma Sadgui | Remote Sensing Awards | Women Researcher Award 

Ms. Oumayma Sadgui, IAV Hassan II, Morocco,

Oumayma Sadgui is a Water and Forest Engineer currently working in Ifrane National Park and pursuing her Ph.D. at IAV Hassan II, specializing in Natural Resources Economics and Environment. With a rich educational background, she holds a State Engineer diploma in forestry economics from the National School of Forest Engineers (ENFI), along with diplomas in general forestry and agronomy. Since 2022, she has been actively involved with the National Water and Forests Agency and the IMU of the PLAR project, focusing on ecotourism development in Ifrane National Park. Oumayma has field experience in surveys, socio-economic and ecological diagnoses, forest inventories, and vegetation studies. She is skilled in statistical data analysis using SPSS, digital cartography (GIS), and remote sensing. Her work is complemented by her ability to lead workshops and training sessions.

Professional Profile:

ORCID

GOOGLE SCHOLAR

Suitability of Oumayma Sadgui for the Research for Women Researcher Award

Academic and Research Background:
Oumayma Sadgui’s strong academic and research background, particularly in natural resources economics and environmental sustainability, makes her a suitable candidate for the award. She holds a Ph.D. candidacy at IAV Hassan II in Natural Resources Economics and has completed significant research on ecosystem services, hydrologic systems, and forest economics. Her focus on economic evaluations of ecosystem services within protected areas like Ifrane National Park demonstrates a clear commitment to research on sustainable development and environmental conservation.

Education

  • 2021-2024: PhD Candidate in Natural Resources Economics and Environment at IAV Hassan II.
  • 2019-2021: State Water and Forest Engineer Diploma, specializing in Forestry Economics from ENFI (National School of Forest Engineers).
  • 2017-2019: Diploma in General Forestry from ENFI.
  • 2015-2017: Two years of preparatory cycle in Agronomy at ENAM.
  • 2014-2015: Baccalaureate (Very Good Honors) in Life and Earth Sciences from Maarabat Boudnib Errachidia High School.

Professional Experience

  • Since 2022: Engineer at the National Water and Forests Agency, involved in the PIAR Project for ecotourism development in Ifrane National Park.
  • 2021: End of study dissertation on the Economic Evaluation of Ecosystem Services in the Toubkal National Park.
  • 2019: Summer Internship at the Provincial Direction of Water and Forests in Casablanca. Participated in an integrated development project in the Ben Slimane region and a multidisciplinary tour in the Middle Atlas and Rif.
  • 2018: Summer Internship at the Regional Direction of Water and Forests in the Middle Atlas. Participated in a multidisciplinary tour in the Middle Atlas and East.
  • 2014: Internship on a farm in Errachidia Province.

Publication top Notes:

Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park

Economic Assessment of Hydrologic Ecosystem Services in Morocco’s Protected Areas: A Case Study of Ifrane National Park

Evaluation and Mapping of Carbon Sequestration Service in Morocco’s Protected Areas : A case study of Ifrnae National Park

Hydrologic Ecosystem Services values in Morocco’s Protected Areas: A Case Study of Ifrane National Park

Impact of land use dynamics on ecosystem services in Ifrane National Park (INP)

 

 

 

Mr. Xiaowo Xu | Remote Sensing award | Best Researcher Award

Mr. Xiaowo Xu | Remote Sensing award | Best Researcher Award 

Mr. Xiaowo Xu, University of Electronic Science and Technology of China 

Xiaowo Xu is a Ph.D. candidate in Information and Communication Engineering at the University of Electronic Science and Technology of China (UESTC), where he has been honing his research skills since September 2022. His academic journey began with a Bachelor of Engineering in Electronic Information Engineering from Sichuan University, followed by a Master of Engineering in the same field at UESTC. His research interests focus on deep learning applications, particularly in object categorization, object detection, instance segmentation, and moving object tracking. Currently, he is dedicated to the intelligent interpretation of synthetic aperture radar (SAR) images. Xiaowo has received several prestigious awards, including the 1st Scholarship for Doctoral Candidates and the Special Scholarship for Doctoral Candidates from UESTC, along with an “Honor Academic” Award and the Outstanding Graduate Student Award for the 2022-2023 academic year.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Xiaowo Xu’s research focus on deep learning applications, particularly in object detection, segmentation, and synthetic aperture radar (SAR) image interpretation, positions him well for the Best Researcher Award. His expertise aligns with cutting-edge areas like object categorization and moving object tracking, essential topics in remote sensing and computer vision, which are currently high-impact fields in academia and industry.

Education:

  • Sep. 2022 – Present: Ph.D. candidate in Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC).
  • Sep. 2020 – Sep. 2022: Master of Engineering in Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC).
  • Sep. 2016 – Jun. 2020: Bachelor of Engineering in Electronic Information Engineering, Sichuan University (SCU).

Work and Research Experience:

  • Ph.D. Research (2022 – Present): Xiaowo Xu is currently pursuing a Ph.D. in Information and Communication Engineering at UESTC, focusing on deep learning applications in synthetic aperture radar (SAR) image intelligent interpretation. His research areas encompass object categorization, detection, instance segmentation, and moving object tracking using deep learning techniques.
  • Master’s Research (2020 – 2022): During his master’s studies at UESTC, he deepened his expertise in information and communication engineering, developing skills in Python, MATLAB, and deep learning frameworks like PyTorch and TensorFlow.
  • Academic Communication and Conferences (2022 – Present): Xiaowo Xu has presented his research through posters at prestigious IEEE conferences, including the International Geoscience and Remote Sensing Symposium and the Radar Conference. His work has been showcased internationally, including in the USA, Malaysia, and China.

Publication top Notes:

A Novel Multimodal Fusion Framework Based on Point Cloud Registration for Near-Field 3D SAR Perception

A Group-Wise Feature Enhancement-and-Fusion Network with Dual-Polarization Feature Enrichment for SAR Ship Detection

RBFA-Net: A Rotated Balanced Feature-Aligned Network for Rotated SAR Ship Detection and Classification

A Sparse-Model-Driven Network for Efficient and High-Accuracy InSAR Phase Filtering

Lite-YOLOv5: A Lightweight Deep Learning Detector for On-Board Ship Detection in Large-Scene Sentinel-1 SAR Images

 

Yongquan Wang | Remote Sensing | Best Researcher Award

Dr.Yongquan Wang | Remote Sensing | Best Researcher Award

PhD at  shenzhen university, China

Yongquan Wang is a dedicated researcher specializing in ocean color and radiative transfer. With a robust academic background, he holds an M.S. and Ph.D. in Urban Informatics from Shenzhen University and a B.S. in Geodesy and Geomatics from Anhui Agriculture University. Recognized as an Outstanding Graduate Student of Guangdong Province, Yongquan’s research focuses on innovative techniques for environmental monitoring, particularly in retrieving oceanic particulate organic nitrogen (PON) concentrations. His work integrates advanced imaging technologies and data processing skills, reflecting a commitment to addressing pressing ecological challenges.

Profile:

Scopus Profile

Strengths for the Award:

Yongquan Wang has demonstrated exceptional research capabilities in the fields of ocean color and radiative transfer. His focus on retrieving oceanic particulate organic nitrogen (PON) concentrations from image data shows innovative thinking and application of advanced techniques. His research work is well-supported by a solid academic background, achieving high GPAs and recognition as an Outstanding Graduate Student of Guangdong Province. The breadth of his publications in reputable journals like IEEE Transactions and Remote Sensing further establishes his expertise. Additionally, his contributions to novel methods using aerial imaging and UAV technology in environmental monitoring underscore his ability to address real-world challenges effectively.

Areas for Improvement:

While Yongquan has made significant strides in his research, he could enhance his impact by diversifying his research collaborations, particularly with interdisciplinary teams that include ecologists and data scientists. Engaging more with broader environmental policy discussions could also strengthen the societal relevance of his work. Additionally, expanding his outreach to communicate research findings to non-specialist audiences may increase public engagement and understanding of his work.

Education:

Yongquan Wang completed his M.S. and Ph.D. at the School of Architecture and Urban Planning, Shenzhen University, where he achieved a GPA of 86.7/100. Prior to this, he earned a B.S. in Geodesy and Geomatics from Anhui Agriculture University, graduating with a GPA of 88.8/100. His educational journey has been marked by academic excellence, including multiple scholarships for outstanding performance. This strong foundation has equipped him with the knowledge and skills to engage in impactful research in ocean color remote sensing and related fields.

Experience:

Yongquan Wang has amassed significant research experience since September 2018, focusing on the retrieval of oceanic particulate organic nitrogen (PON) concentrations from image data. He has explored the development of retrieval models for global ocean monitoring and atmospheric corrections under weak light conditions. Additionally, he has engaged in innovative projects using tethered UAVs for emergency surveying and mapping, demonstrating versatility in applying technology to real-world problems. His work reflects a commitment to advancing remote sensing methodologies for environmental applications.

Research Focus:

Yongquan’s research centers on ocean color and radiative transfer, particularly the retrieval of oceanic particulate organic nitrogen (PON) concentrations. He investigates bio-optical proxies for PON retrieval and develops models to analyze monthly variations in global ocean PON levels. His work also addresses atmospheric correction techniques in optically complex waters, enhancing the accuracy of remote sensing data. By leveraging advanced imaging technologies and data processing skills, Yongquan aims to contribute valuable insights into oceanic health and environmental sustainability.

Publications Top Notes:

  1. Towards Applicable Retrieval Models of Oceanic Particulate Organic Nitrogen Concentrations for Multiple Ocean Color Satellite Missions 📄
  2. Ocean Colour Atmospheric Correction for Optically Complex Waters under High Solar Zenith Angles: Facilitating Frequent Diurnal Monitoring and Management 🌊
  3. Remote Sensing Video Production and Traffic Information Extraction Based on Urban Skyline 🚦
  4. Spatiotemporal Dynamics and Geo-environmental Factors Influencing Mangrove Gross Primary Productivity during 2000–2020 in Gaoqiao Mangrove Reserve, China 🌳
  5. Estimating Particulate Organic Nitrogen Concentrations in the Surface Ocean from Ocean Color Remote Sensing Data 🔍
  6. Satellite Retrieval of Oceanic Particulate Organic Nitrogen Concentration 🌐
  7. A Glimpse of Ocean Color Remote Sensing From Moon-Based Earth Observations 🌙
  8. Framework to Create Cloud-Free Remote Sensing Data Using Passenger Aircraft as the Platform ✈️
  9. Dynamic Earth Observation Based on an Urban Skyline: A New Remote Sensing Approach for Urban Emergency Response 🏙️
  10. Volunteered Remote Sensing Data Generation with Air Passengers as Sensors 🚁

Conclusion:

Yongquan Wang is a strong candidate for the Research for Best Researcher Award, with notable achievements and contributions in oceanographic research. His innovative approaches and demonstrated academic excellence position him well for recognition. Continued efforts to broaden his collaboration network and enhance public engagement will further solidify his status as a leading researcher in his field.

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