SCC-IRG JST: Multimodal Data Analytics and Integration for Effective COVID-19, Pandemics and Compound Disaster Response and Management
Lead PI:
Shu-Ching Chen
Abstract

The COVID-19 pandemic has resulted in huge amounts of confirmed cases and deaths both in the United States and globally. The nation experienced grave repercussions to citizens’ lives, health, and the economy. Due to its high contagiousness, policies such as quarantine and lockdowns were put in place to slow the virus’ rapid spread. Some major challenges are identifying vulnerable communities to provide immediate help and determining policies that are effective in slowing down the spread with minimal adverse effects on people’s livelihood, mental health, and the economy. This project aims to develop tools that can locate communities in crisis, identify their problems and demands, and predict pandemic transmission trends and impacts in diverse communities based on mobility and social media data. The developed tools and technologies are critical for effective disaster management and pandemic recovery. Furthermore, pandemic and other natural disasters’ co-occurrence is even more challenging given that mass evacuation and sheltering processes may cause a spike in cases of transmissible pandemic diseases. This project will develop new technologies that can aid emergency managers under a pandemic scenario based upon our previously developed tools for natural disaster management.

The proposed research provides potential solutions to solve crucial disaster information management challenges for COVID-19, future pandemics, and compound disasters while leveraging the team's previous work. Furthermore, the proposed techniques will help better understand the disaster situation to assist the preparation and recovery for a broad range of communities, including minority and low-income populations. This project will also have the potential to have societal and economic impacts by providing the most accurate information on pandemics and compound disasters to prevent unexpected losses. The developed solutions could be later expanded for other disaster and information management. This project fosters collaboration between the Florida International University (FIU) and the University of Tokyo, as well as institutions across the public and private sectors (including the cities of Miami-Dade, Florida, and Tokyo, Japan), to develop advanced techniques for effective emergency response and management for COVID-19, future pandemic, and compound disasters. This work’s broader impact is aligned with the national goal of building smart and connected communities by developing innovative disaster information exchange and analysis tools with real-life data. In addition, FIU is one of the nation’s leading minority-serving research universities and ranks first in awarding undergraduate and graduate degrees to Hispanic students. The research findings of this project will be disseminated through workshops, publications, and presentations.

This project is a joint collaboration between the National Science Foundation and the Japan Science and Technology Agency.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Shu-Ching Chen
Dr. Shu-Ching Chen is the inaugural Executive Director of Data Science and Analytics Innovation Center (dSAIC). dSAIC is a multi-university center and based at the University of Missouri-Kansas City (UMKC). He provides the expertise and leadership to ensure the Center’s overarching aspiration to become Missouri’s hub for innovative research and expertise in data science, analytics, data protection (cybersecurity), artificial intelligence, and machine learning solving critical societal problems, being a state-of-the-art resource for industry and the UM universities, producing a skilled workforce to meet growing industry demands and spurring economic development becomes a reality. Dr. Chen has received many research grants from NSF, National Oceanic and Atmospheric Administration (NOAA), Department of Homeland Security (DHS), National Institute of Health (NIH), Department of Energy (DOE), Army Research Office (ARO), Naval Research Laboratory (NRL), Environmental Protection Agency (EPA), Florida Office of Insurance Regulation, Florida Department of Transportation, IBM, and Microsoft. Dr. Chen was named a 2011 recipient of the ACM Distinguished Scientist Award. He received the best paper awards from 2006 IEEE International Symposium on Multimedia and 2016 IEEE International Conference on Information Reuse and Integration. He also received the best student paper award from 2022 IEEE International Conference on Multimedia Information Processing and Retrieval. He received the 2019 Service Award from IEEE Computer Society’s Technical Committee on Multimedia Computing. He was awarded the IEEE Systems, Man, and Cybernetics (SMC) Society's Outstanding Contribution Award in 2005 and was the co-recipient of the IEEE Most Active SMC Technical Committee Award in 2006. He is a fellow of IEEE, AAAS, AAIA, and SIRI.
Performance Period: 10/01/2022 - 03/31/2025
Institution: University of Missouri-Kansas City
Award Number: 2301552