Dr. Xing WANG received his Ph.D. in Cartography and Geographic Information Systems in September 2022. During his doctoral studies, he was a visiting researcher at the University of Vienna, Austria (Mar 2021–Jun 2022), focusing on intelligent processing, spatiotemporal analysis, and high-precision retrieval of atmospheric observation data. Since 2023, he has been a postdoctoral researcher at the School of Atmospheric Sciences, Nanjing University. His research focuses on advancing atmospheric sciences and meteorological information processing by integrating atmospheric science with artificial intelligence methods (machine learning, deep learning, and large multimodal foundation models) and geospatial analysis. His main research interests include: Quantitative precipitation estimation and microphysical retrieval: designing algorithms for precise estimation of precipitation amount, raindrop size distribution, and hydrometeor phase using ground stations, disdrometers, Doppler radar, and multi-source satellite data. High spatiotemporal resolution urban meteorological monitoring: building integrated systems combining ground sensors, radar measurements, and satellite-based sensing to capture fine-scale urban meteorological phenomena. Citizen science-driven precipitation observation: exploring low-cost, scalable precipitation monitoring using smart devices, crowdsourced sensors, and participatory data quality control to expand coverage in under-observed regions.