Zhongying (Stephen) Wang
Hi there! 😃
My name is Zhongying and I am a fifth-year PhD candidate in Geography at the University of Colorado Boulder, supervised by Prof. Morteza Karimzadeh at the GeoHAI Lab. My work lies at the intersection of AI and Geography (GeoAI). My research focuses on GeoAI methods for environmental health and public health applications. In particular, I work on high-resolution air pollution estimation using satellite, ground and simulation data; spatiotemporal deep learning and data fusion for geospatial prediction; and geospatial foundation models and pretrained location encoders.
news
| Apr 3, 2023 |
Aerosol Optical Depth Imputation work is accepted to IGARSS 2023! |
|---|---|
| Mar 26, 2023 | Presented PM2.5 estimation work at AAG 2023 in Denver. |
| Nov 7, 2015 | A long announcement with details |
selected publications
-
The United States COVID-19 Forecast Hub DatasetScientific Data, 2022
-
Sensitivity Analysis for COVID-19 Epidemiological Models Within a Geographic FrameworkIn Proceedings of the 1st ACM SIGSPATIAL International Workshop on Modeling and Understanding the Spread of COVID-19, 2020
-
Integrating Spatiotemporal Features in LSTM for Spatially Informed COVID-19 Hospitalization ForecastingInternational Journal of Geographical Information Science, 2025Advance online publication
-
High-Resolution Estimation of Daily PM2.5 Levels in the Contiguous US Using Bi-LSTM with AttentionRemote Sensing, 2025
-
Performance and Generalizability Impacts of Incorporating Geolocation into Deep Learning for Dynamic PM2.5 EstimationGIScience and Remote Sensing, 2025In press; also available as arXiv:2505.18461
-
Respiratory Exacerbations Increase with Chronic PM2.5 Exposure in Current and Former SmokersmedRxiv, 2025medRxiv preprint