Name
P26 NSF CREST Center for Geospatial and Environmental Informatics, Modeling and Simulation on Coastal Resilience.
Description

The CREST Center for Geospatial and Environmental Informatics, Modeling and Simulation (CREST GEIMS) is funded by the NSF Award No. 211263 for 15 December 2021 – 30 November 2026. The CREST GEIMS recruits and supports underrepresented minority (URM) students to pursue degrees in STEM areas, focusing on coastal resilience. The center conducts cutting-edge research through three integrated subprojects to address the challenges we face in coastal communities impacted by climate change. Subproject 1 is developing a new approach integrating remote and autonomous sensing with geospatial computing and artificial intelligence (AI) to improve coastal zone monitoring and resiliency decision-making. It generates detailed and accurate geographic information systems data for the characterization of the built and natural environment. Results are being integrated into subprojects 2 and subproject 3. Subproject 2 is developing a better understanding of the urban water cycle and the resilience of water infrastructure through integrated characterization, simulation, and assessments. Subproject 3 investigates how emerging data sources and advanced geospatial computing can be applied to evaluate, assist, and improve a coastal community’s physical, behavioral, and social health after disasters. Subprojects 1, 2, and 3 collaborate in developing the modeling and simulation. The center is also developing enabling technologies for sensing and environment monitoring through basic research and innovation in AI-drone and IoT. The center adopts a student-centered mentoring and advising approach, tailored to each student, and guides the students in their doctoral studies. The center has established two CREST GEIMS WIT (Workforce Industry Training) programs at two local high schools, and an after-school robotics program in an elementary school. The WIT program is expanded to include two more high schools starting in fall 2023.

Lea-Dear Chen
Time
3:30 PM - 4:45 PM
Session Type
Poster
Presentation Type
In Person
Location Name
2nd Floor Foyer