Cyberinfrastructure and Data-Intensive Research
The research group is part of the National Science Foundation
$3 Million "MIR Fostering Accelerated Sciences Transformation Education and Research Program"
$10 Million "Category II: ACES - Accelerating Computing for Emerging Sciences" programs.
The research group has also developed a high-performance computer cluster based on advanced cyberinfrastructure and the latest docker technologies to host a massive amount of spatial data and computation power
Check our BluPix application at : https://blupix.geos.tamu.edu
With the increased frequency of natural hazards, disasters, and consequent massive losses, there is a critical need for building urban resilience and improving urban sustainability. Spatial decision support systems (SDSSs) have been well studied in the context of GIS and various related domains. New challenges and opportunities have arisen with regard to transforming SDSSs into intelligent capabilities for complex geospatial problem-solving and decision-making. The research group investigates intersections between GIScience, Decision Science, and Cyberinfrastructure to build scalable, high-performance, and open decision support software tools to support intelligent spatial decision-making in various application domains (e.g., disaster management, water resources management, agriculture risk management, national security, and critical infrastructure protection). Our research involved several inter-related sub-research themes:
1. Cyberinfrastructure and data-intensive research
2. Human-centered decision-making
3. Spatial uncertainty analysis and modeling
4. Social sensing and human knowledge acquisition
5. Human environment interactions
6. Spatiotemporal data modeling and population dynamics
7. Disaster management
We are actively recruiting M.S. and Ph.D. graduate students who are interested in Geographic Information Science and Systems, Geo-computation, spatial decision-making, and data-Intensive research. Financial support and/or research/teaching assistantships are available to qualified students. If you are interested, please contact Dr. Zhe Zhang via email email@example.com
[Publication- October 2021] Mr. Ziyi Zhang's paper has been accepted by 2021 ACM Sigspatial workshop! Congratulations!
[Funding Award- September 2021] Dr. Zhang, Sole PI, National Geographic Society Education Grant!
[Funding Award- September 2021] Dr. Zhang, Co-PI, NSF Convergence Accelerator Track E: Combining high-resolution climate simulations with ocean biogeochemistry, fisheries and decision-making models to improve sustainable fisheries, $749,548, National Science Foundation-Office of Integrative Activities
[Funding Award-September 2021] Dr. Zhang, Co-I , Category II: ACES - Accelerating Computing for Emerging Sciences, $ 10,000,000, National Science Foundation-Office of Advanced Cyberinfrastructure.
[Publication - August 2021] Dr. Zhang has organized a special issue titled "Cyberinfrastructure and Intelligent Spatial Decision Support Systems" in Transactions in GIS journal.
Zhang, Zhe, Lei Zou, Wenwen Li, Lynn Usery, Jochen Albrecht, and Marc Armstrong., 2021. Cyberinfrastructure and intelligent spatial decision support systems, Transactions in GIS, 25(4), 1651-1653.
[Conference presentation- July 2021] Graduate student Mr. Shuyang Zhang gave a talk at the 46th Annual Natural Hazards Research and Applications Workshop.Watch his talk at: https://youtu.be/YV-Z_a52-rc
[Software - July 2021] CIDI-Spatial Lab has developed a computer cluster based on the advanced cyberinfrastructure. The BluPix app is now hosted by our cyberinfrastructure cluster at:
[Invited Talk- June 2021] Dr. Zhang and graduate student Mr. Diya Li were invited to give a talk at Texas A&M High Performance Research Computing Center on a K-12 summer camp.
[Invited Talk- May 2021] Dr. Zhang were invited to give a talk at Texas A&M GeoX Summer Camp.
[Article Accepted - Jan 2021] Two articles were published.
Jiang, H., Hu, H., Li, B., Zhang, Z., Wang, S. and Lin, T., 2021. Understanding the non-stationary relationships between corn yields and meteorology via a spatiotemporally varying coefficient model. Agricultural and Forest Meteorology, 301, p.108340.
Li, Yao, Huilin Gao, George H. Allen, and Zhe Zhang. "Constructing Reservoir Area–Volume–Elevation Curve from TanDEM-X DEM Data." IEEE journal of selected topics in applied earth observations and remote sensing 14 (2021): 2249-2257.
[Funding Award- Jan 2021] Dr. Zhe Zhang, Co-PI, Impact of COVID-19 Induced Active Transportation Demand on the Built Environment and Public Health, $90,000, US Department of Transportation
[Funding Award- December 2020] Dr. Zhe Zhang, PI, Texas A&M President’s Excellence Fund: T3 Grant, Human-Centered Decision Support System for Improving Urban Resilience in Disaster Management: $32,000
[Funding Award - Sep 2020] Dr. Zhang, PI, Texas A&M TAMIDS Data Resource Development Program
A Spatial Decision Support System for Cardiovascular Disease Risk Assessment in Response to the COVID-19 Crisis: $27,000.
[Funding Award - Sep 2020] Dr. Zhang, PI, An Intelligent Spatial Decision Support System based on Citizen Science for Driving Resilience in Coastal Communities, $20,000, Texas A&M School of Innovation- Innovation [X].
[Funding Award - Sep 2020] Dr. Zhang, Co-PI, MRI: Acquisition of FASTER - Fostering Accelerated Sciences Transformation Education and Research, $3,090,000, National Science Foundation
[Funding Award- Sep 2020] Dr. Zhang, PI, K-12 Geography and GIS education program- Texas Youth Action Network, $10,000, Texas Department of State Health Services
[Funding Award - Sep 2020] Dr. Zhang, Co-PI, A Hybrid Decision Support System for Driving Resiliency in Texas Coastal Communities, $300,000, NOAA
[Funding Award - June 2020] Dr. Zhang, PI, Social Vulnerability, Mobility, and COVID-19 Spatial Mortality Patterns, $1000, National Science Foundation- Natural Hazard Center.
[Software- July 2020] The research group developed a Health Space & Time Web App.
The app illustrates the number of COVID-19 confirmed cases at a spatiotemporal scale for the United States. It also demonstrates the spatiotemporal depressive symptoms caused by COVID-19 using social media data mining. The Health Space & Time application is available from here: https://arcg.is/1qmSqi
[Publication- July 2020] Graduate student Mr. Diya Li published a paper.
Li, D., Chaudhary, H., and Zhang, Z., 2020. Modeling Spatiotemporal Pattern of Depressive Symptoms Caused by COVID-19 Using Social Media Data Mining. International Journal of Environmental Research and Public Health, 17(14), 4988.
[Seminar - Feb 2020] Dr. Michael Goodchild came to visit our lab and gave a talk on Convergent GIScience.