About Shaowen Wang
Bio
Shaowen Wang is a Professor and Head of the Department of Geography and Geographic Information Science; Richard and Margaret Romano Professorial Scholar; and an Affiliate Professor of the Department of Computer Science, Department of Urban and Regional Planning, and School of Information Sciences at the University of Illinois at Urbana-Champaign (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 (NCSA) for CyberGIS from 2010 to 2017 and Lead of NCSA’s Earth and Environment Theme from 2014 to 2017. His research interests include geographic information science and systems (GIS), advanced cyberinfrastructure and cyberGIS, complex environmental and geospatial problems, computational and data sciences, high-performance and distributed computing, and spatial analysis and modeling. His research has been actively supported by a number of U.S. government agencies (e.g., CDC, DOE, EPA, NASA, NIH, NSF, USDA, and USGS) and industry. He has served as the principal investigator of several multi-institution projects sponsored by the National Science Foundation (NSF) for establishing the interdisciplinary field of cyberGIS and advancing related scientific problem solving in various domains (e.g., agriculture, bioenergy, emergency management, geography and spatial sciences, geosciences, and public health). He has published 150+ peer-reviewed papers including articles in 40+ journals. 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 served on the University Consortium for Geographic Information Science’s (UCGIS) board of directors from 2009 to 2012 and President of UCGIS from 2016 to 2017. He served on the advisory board of the NSF Extreme Science and Engineering Discovery Environment (XSEDE) program from 2016 to 2018. He served 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 was a visiting scholar at Lund University, sponsored by NSF in 2006, and a NCSA fellow in 2007. He received the NSF CAREER Award in 2009. He was named a Helen Corley Petit Scholar for 2011-2012 and Centennial Scholar for 2013-2016 by UIUC’s College of Liberal Arts and Sciences.
Education
- PhD, Geographic Information Science, University of Iowa (2004)
- MCS, Computer Science, University of Iowa (2002)
- MS, Geography, Peking University (1998)
- BS, Computer Engineering, Tianjin University, China (1995)
Research and publications
Ongoing and upcoming research
Research Interests
Shaowen Wang is trained as both a geographer and computer scientist. His research interests center on three interrelated themes: 1) computational and geographic information sciences; 2) advanced cyberinfrastructure, cyberGIS, and geospatial data science; and 3) multi-scale geospatial problem solving and spatiotemporal analytics. He has published numerous peer-reviewed papers including articles in more than 20 journals (e.g., Annals of the American Association of Geographers, BioScience, Computers and Geosciences, International Journal of Geographical Information Science, Parallel Computing, and Proceedings of the National Academy of Sciences). He led the development of the Open Science Grid Generic Information Provider that has been widely used. He has also led several multi-institution projects to advance cyberGIS and related scientific problem solving. Wang invented and has been leading the research and development of GISolve Toolkit that represents cutting-edge software for cyberGIS integration and applications (e.g., in agriculture, bioenergy, emergency management, geography and social sciences, geosciences, and public health). He was the founding manager of the Grid Research and educatiOn group @ ioWa (GROW) to foster computational science research and education by a multidisciplinary team within several Iowa higher education institutions. Currently, he is the founding director of the CyberInfrastructure and Geospatial Information Laboratory (CIGI Laboratory) and CyberGIS Center for Advanced Digital and Spatial Studies (CyberGIS Center) at the University of Illinois at Urbana-Champaign.
Summary of Extramural Research Funding: (received from the U.S. National Science Foundation (NSF), Centers for Disease Control and Prevention (CDC), Department of Energy (DOE), Environmental Protection Agency (EPA), National Aeronautics and Space Administration (NASA), U.S. Department of Agriculture (USDA), U.S. Geological Survey (USGS), and industry): Principal Investigator (PI) for more than $15 million competitive research grants; PI for tens of millions of normalized computing hours of NSF supercomputing resources; and Co-PI and investigator for contributing to sponsored research with tens of millions of U.S. dollars.
Selected publications
Choi, Y. D., Goodall, J. L., Sadler, J. M., Castronova, A. M., Bennett, A., Li, Z., Nijssen, B., Wang, S., Clark, M. P., Ames, D. P., Horsburgh, J. S., Yi, H., Bandaragoda, C., Seul, M., Hooper, R., & Tarboton, D. G. (2021). Toward open and reproducible environmental modeling by integrating online data repositories, computational environments, and model Application Programming Interfaces. Environmental Modelling and Software, 135, [104888]. https://doi.org/10.1016/j.envsoft.2020.104888
Wang, S., Lyu, F., Wang, S., Catlet, C. E., Padmanabhan, A., & Soltani, K. (Accepted/In press). Integrating CyberGIS and Urban Sensing for Reproducible Streaming Analytics. In W. Shi, M. Goodchild, M. Batty, M-P. Kwan, & A. Zhang (Eds.), Urban Informatics (The Urban Book Series). Springer Singapore.
Davis, A. V., & Wang, S. (Accepted/In press). A Concurrent Entity Component System for Geographical Wildlife Epidemiological Modeling. Geographical Analysis. https://doi.org/10.1111/gean.12258
Jiang, H., Hu, H., Zhong, R., Xu, J., Xu, J., Huang, J., Wang, S., Ying, Y., & Lin, T. (2020). A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level. Global change biology, 26(3), 1754-1766. https://doi.org/10.1111/gcb.14885
Jiang, H., Hu, H., Wang, S., Ying, Y., & Lin, T. (2020). Understanding the impact of sub-seasonal meteorological variability on corn yield in the U.S. Corn Belt. Science of the Total Environment, 724, [138235]. https://doi.org/10.1016/j.scitotenv.2020.138235
Teaching and advising
Classes taught
- GEOG 595: Advanced Digital and Spatial Studies
- GEOG 480: Principles of GIS
- GEOG 479: Advanced GIS
- GEOG 407: Foundations of CyberGIS and Geospatial Data Science
- GEOG 379: Introduction to Geographic Information Systems