| Prof. Kegen Yu, IEEE Senior MemberChina University of Mining and Technology, China Prof. Kegen Yu received the PhD degree in electrical engineering from The University of Sydney, Australia, in 2003. He has worked for universities and research institutions in Australia, China and Finland. He is currently a Distinguished Professor with China University of Mining and Technology, Xuzhou, China. Prof. Yu has co-authored the book "Ground-Based Wireless Positioning" (Wiley-IEEE Press, 2009) and another book titled "Wireless Positioning: Principles and Practice" (Springer, 2018). Additionally, he authored the book "Theory and Practice of GNSS Reflectometry" (Springer, 2021). He has contributed to over 200 refereed journal and conference articles, including more than 70 articles published in IEEE journals. He was ranked in the world’s top 2% scientists list in 2022 by Stanford University and Elsevier. His research interests include GNSS-R, wireless positioning, and remote sensing. |
| Prof. Bruce MelvilleThe University of Auckland Yong Wang received the Ph.D. degree in computer science and technology from the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China, in 2008. He is currently an Associate Professor with the School of Computer Science and Engineering, University of Electronic Science and Technology of China. His research interests include spatial database, spatial query processing, and privacy enhancing technologies. |
| Prof. Mahmoud Reza DelavarUniversity of Tehran, Iran Prof. Mahmoud Reza Delavar is Director, Center of Excellence in Geomatic Eng. in Disaster Management and Director, Land Administration in Smart City Lab., School of Surveying and Geospatial Eng., College of Engineering, University of Tehran. Dr. Delavar has received his BSc. in Civil Eng.-Surveying from Technical University of KNT, Tehran, Iran in 1989, MSc in Civil Eng. - Photogrammetry and Remote Sensing from University of Roorkee (Currently IIT Roorkee), Roorkee, India in 1992 and a PhD in Geomatic Eng.-GIS from University of New South Wales (UNSW), Sydney, Australia in 1997. He was the chair of International Society of Photogrammetry and Remote Sensing ISPRS WG IV/3 (Spatial Statistics, Analysis and Uncertainty Modeling) during 2016- 2022, chair of ISPRS WG IV/2 (Artificial Intelligence and Uncertainty Modeling in Spatial Analysis) during 2022-2024 and is the advisor of the same working group during 2024-2026. He is Iran's national representative to International Society of Urban Data Management (UDMS) since 2006. Prof. Delavar is founder of Iranian Society of Surveying and Geomatics Eng. (ISSGE) and is in the editorial board of ISPRS International Journal of Geo-Information (IJGI) and Geo-spatial Information Science (GSIS). Prof. Delavar is a member of International Society of Urban Informatics. Prof. Delavar has published 404 papers in reputable national and international conferences and Journals. Prof. Delavar has supervised 124 MSc. and PhD theses and Postdoc research so far. His research interests are in spatial data quality and uncertainty modeling, temporal GIS, disaster management, smart cities, cadaster, land administration, spatial data infrastructure (SDI), building information modeling/management, (BIM), multi-dimensional GIS, ubiquitous GIS, spatial interoperability, spatial data fusion, spatial data science, intelligent GIS, urban growth modeling, land use and land cover change modeling, and integration of remote sensing and GIS. |
| Prof. Zhi Gao, IEEE MemberWuhan University, China Zhi Gao (Member, IEEE) received the B.Eng. and Ph.D. degrees from Wuhan University, Wuhan, China, in 2002 and 2007, respectively.,In 2008, he joined the Interactive and Digital Media Institute, National University of Singapore (NUS), Singapore, as a Research Fellow (A) and the Project Manager. In 2014, he joined Temasek Laboratories, NUS (TL@NUS), as a Research Scientist (A) and a Principal Investigator. He is currently working as a Full Professor with the School of Remote Sensing and Information Engineering, Wuhan University. He has published more than 70 research papers in top journals and conferences, such as International Journal of Computer Vision (IJCV), IEEE Transactions on Pattern Analysis on and Machine Intelligence (TPAMI), IEEE Transactions on Industrial Electronics (TIE), IEEE Transactions on Geoscience and Remote Sensing (TGRS), IEEE Transactions on Intelligent Transportation Systems (TITS), ISPRS Journal of Photogrammetry and Remote Sensing (JPRS), Neurocomputing, IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), the Conference on Computer Vision and Pattern Recognition (CVPR), the European Conference on Computer Vision (ECCV), Asian Conference on Computer Vision (ACCV), and British Machine Vision Conference (BMVC). Since 2019, he has been supported by the Distinguished Professor Program of Hubei Province and the National Young Talent Program, China. His research interests include computer vision, machine learning, and remote sensing and their applications. In particular, he has a strong interest in vision for intelligent systems and intelligent system-based vision.,Dr. Gao serves as an Associate Editor for the Unmanned Systems journal. |
| Prof. Yuan WangNanjing University of Information Science and Technology, China Li Xiaowen Remote Sensing Science Youth Award (5 winners nationwide every 2 years); MDPI Remote Sensing Best PhD Thesis Award (1 winner globally each year); International Society for Atmospheric Environment Remote Sensing (ISAERS) China Outstanding Doctoral Dissertation Award (5 winners nationwide annually); Led or participated in multiple national and provincial/ministerial-level research projects. Published over 30 academic papers, including 3 EI conference papers. As first/corresponding author, published more than 10 SCI papers in journals such as Nature Communications, Earth System Science Data, and ISPRS Journal of Photogrammetry and Remote Sensing, including 7 Q1 TOP papers, 3 Q2 TOP papers, and 5 papers with an impact factor (IF) > 10. Research Interests: Remote sensing quantitative retrieval and prediction of atmospheric environmental parameters; Development of global high-resolution, long-term, seamless atmospheric environmental parameter products; Population exposure and health risk assessment of atmospheric environmental factors. |
