Shaowen Wang is Professor and Head of the Department of Geography and Geographic Information Science; and Affiliate Professor of the Department of Computer Science, Department of Urban and Regional Planning, and School of Information Sciences at the University of Illinois Urbana-Champaign (UIUC). He is a Faculty Fellow of the Office of the Vice Chancellor for Research and Innovation at UIUC. He has served as Founding Director of the CyberGIS Center for Advanced Digital and Spatial Studies at UIUC since 2013. He served as Associate Director of the National Center for Supercomputing Applications for CyberGIS from 2010 to 2017.
His research interests include geographic information science and systems (GIS), advanced cyberinfrastructure and cyberGIS, complex social and environmental problems, computational and data sciences, geospatial science and technology, high-performance and distributed computing, and spatial analysis and modeling. He has received research funding from several U.S. federal and state agencies (e.g., CDC, DOE, Illinois EPA, NASA, NIH, NSF, USDA, and USGS) and industry, and served as the Principal Investigator (PI) of more than $30 million competitive research grants. He currently serves as the PI and Director of the NSF Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE). He has published over 180 peer-reviewed papers & reports and edited or co-edited several books and proceedings. He has served as an action editor of GeoInformatica, associate editor of SoftwareX, and guest editor or editorial board member for multiple other journals, book series, and proceedings.
He received the NSF CAREER Award in 2009. He was named a Helen Corley Petit Scholar for 2011-2012, Centennial Scholar for 2013-2016, and Richard and Margaret Romano Professorial Scholar for 2018-2021 by UIUC’s College of Liberal Arts and Sciences. He is a Fellow of the American Association for the Advancement of Science (AAAS) and Fellow of the American Association of Geographers (AAG). He received the 2022 AAG Distinguished Scholarship Honors. He served as President of the University Consortium for Geographic Information Science from 2016 to 2017, and as a member of the Board on Earth Sciences and Resources of the National Academies of Sciences, Engineering, and Medicine from 2015 to 2020. He has supervised more than 30 PhD students and postdoctoral fellows, and many of his advisees are holding positions at major research universities, premier research and development laboratories, and leading geospatial companies.
- PhD, Geography, the University of Iowa
- Master of Computer Science, the University of Iowa
- MS, Geography, Peking University
- BS, Computer Engineering, Tianjin University
- GGIS 595 - Advanced Digital and Spatial Studies
- GGIS 480 - Principles of GIS
- GGIS 479 - Advanced GIS
- GGIS 407 - Foundations of CyberGIS and Geospatial Data Science
- GGIS 379 - Introduction to GIS
Additional Campus Affiliations
Professor, School of Information Sciences
Professor, Computer Science
New Frontiers Initiative Faculty Fellow, Office of the Vice Chancellor for Research and Innovation
Baig, F., Michels, A., Xiao, Z., Han, S. Y., Padmanabhan, A., Li, Z., & Wang, S. (2022). CyberGIS-Cloud: A unified middleware framework for cloud-based geospatial research and education. In PEARC 2022 Conference Series - Practice and Experience in Advanced Research Computing 2022 - Revolutionary: Computing, Connections, You  (PEARC 2022 Conference Series - Practice and Experience in Advanced Research Computing 2022 - Revolutionary: Computing, Connections, You). Association for Computing Machinery, Inc. https://doi.org/10.1145/3491418.3535148
Fu, P., Jaiswal, D., McGrath, J. M., Wang, S., Long, S. P., & Bernacchi, C. J. (2022). Drought imprints on crops can reduce yield loss: Nature's insights for food security. Food and Energy Security, 11(1), [e332]. https://doi.org/10.1002/fes3.332
Guo, C., Hu, H., Wang, S., Rodriguez, L. F., Ting, K. C., & Lin, T. (2022). Multiperiod stochastic programming for biomass supply chain design under spatiotemporal variability of feedstock supply. Renewable Energy, 186, 378-393. https://doi.org/10.1016/j.renene.2021.12.144
Jiang, Z., He, W., Kirby, M. S., Sainju, A. M., Wang, S., Stanislawski, L. V., Shavers, E. J., & Usery, E. L. (2022). Weakly Supervised Spatial Deep Learning for Earth Image Segmentation Based on Imperfect Polyline Labels. ACM Transactions on Intelligent Systems and Technology, 13(2), . https://doi.org/10.1145/3480970
Kang, J. Y., Michels, A., Crooks, A., Aldstadt, J., & Wang, S. (2022). An Integrated Framework of Global Sensitivity Analysis and Calibration for Spatially Explicit Agent-based Models. Transactions in GIS, 26(1), 100-128. https://doi.org/10.1111/tgis.12837