Teaming for Interdisciplinary Research Pre-Seed Program

Many communities in the US and around the globe are facing increasing threats from anthropogenic climate change including flooding, wildfires, water quality degradation and heat hazards. Building resilient communities that can effectively overcome these threats requires a multi-pronged approach. While traditional approaches have been successful in addressing these challenges at local scales, there are practical limitations in operationalization of these models at regional or global scales. Recent dramatic advancements in data-driven technologies such as artificial intelligence (AI), deep learning, Internet-of-Things (IoT), and cloud computing have the potential to radically transform traditional approaches to enhance community resilience.

This project will create a multidisciplinary working group to expand the conceptualization and operationalization of resilient communities through a “bi-lingual” dialogue between natural/physical science researchers and data science researchers. This group will work towards laying a strong edifice for conducting exploratory research towards addressing increasingly intensifying vulnerabilities of communities by combining traditional physical/natural science and engineering approaches with modern data-driven technologies. We will study the complex challenges involved in building robust data science driven frameworks that incorporate privacy-aware participatory sensing, IoT, cloud and edge computing, data integration and fusion, statistical and deep learning to tackle environmental grand challenges of the next decade. Furthermore, this project will outline a flexible yet robust cloud-based architecture for a data science-driven community resilience system. This layered plug-and-play architecture will support modules to seamlessly ingress data from diverse sources, integrating heterogeneous data, deriving explainable and actionable intelligence at multiple spatio-temporal scales, and adapting these modules to optimize them for multiple distinct resilience applications.

Team Lead

Lakshmish Ramaswamy
Department of Computer Science
laksmr@uga.edu

Team Members

Nandita Gaur
Department of Soil and Crop Sciences

Andrew Grundstein
Department of Geography

In Kee Kim
Department of Computer Science

Sung-Hee “Sonny” Kim
School of Environmental, Civil, Agricultural and Mechanical Engineering

Jaewoo Lee
Department of Computer Science

Kyu H. Lee
Department of Computer Science

Sheng Li
Department of Computer Science

Deepak Mishra
Department of Geography

Cheolwoo Park
Department of Statistics

Alicia Peduzzi
School of Forestry and Natural Resources

Lori Sutter
School of Forestry and Natural Resources