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NSF awards grant to College of Engineering to help improve disaster management and pandemic recovery

NSF awards grant to College of Engineering to help improve disaster management and pandemic recovery

March 16, 2022 at 3:04pm

By Adrienne Sylver

To improve disaster response and gain a better understanding of a population’s needs and behaviors during a crisis, Florida International University’s College of Engineering and Computing has received a $750,000 National Science Foundation (NSF) grant.

FIU researchers are working closely with counterparts at the University of Tokyo, who received a similar grant from the Japan Science and Technology Agency. Together, the scientists hope to develop the critical tools and technologies necessary for effective disaster management and pandemic recovery.

Shu-Ching Chen, professor and director of the Distributed Multimedia Information Systems Laboratory at FIU, is the principal investigator, and Steven Luis, executive director for technology at FIU’s College of Engineering and Computing, is co-principal investigator. The two have worked on numerous disaster information initiatives.

“What’s really interesting about our collaboration with Japan is that we have the opportunity to look closely at the different cultures and locations, to challenge assumptions and ultimately create systems that help us manage disaster events in a way that we hope can be used throughout the world,” Chen said.

The research is part of the NSF’s Smart & Connected Communities (SCC) program, designed to develop more smart cities that can use data to improve their safety, health, security, economic vitality and overall quality of life.

The project, “SCC-IRG JST: Multimodal Data Analytics and Integration for Effective COVID-19, Pandemics and Compound Disaster Response and Management,” is possible in part because of FIU’s vast experience with hurricane modeling. Chen is the co-PI and leader of the computer science component of the Florida Public Hurricane Loss Model, which brings together a multidisciplinary team of meteorologists, wind and structural engineers, computer science, statistics, finance and actuarial science experts. Japan’s experience with earthquakes and tsunamis adds another element to the work.

Visual schema of the proposed data acquisition, analysis, and their applications for disaster response and management


“We are applying machine learning algorithms using cell phone mobility and social media data sets to potentially understand and predict evacuation patterns,” Luis said. “In Japan, when an evacuation is issued, people tend to evacuate by foot and by public transportation. In Florida, six million people jump in their cars at the same time.”

The project will look closely at “crisis communities,” identifying and predicting behaviors to establish better situational awareness, informing emergency managers and decision-makers where to target solutions.

While FIU researchers have specialization in analyzing social media data, their Japan colleagues are adept at mobility data. The public is becoming more familiar with the use of information in both areas, particularly since the COVID-19 pandemic brought about a need for population health tracking and information management.

With improvements in mobile phone technology, data scientists can advise best evacuation routes, for example, down to the neighborhood level, when an event is predicted or has occurred. They can also quickly correct misinformation or direct specific messages to those most in need.

“It’s a little bit like being a detective,” Luis said of the investigation. “We are gathering data resources and using computers and algorithms to help us pull together and interpret the clues.”

This is not the first collaboration between FIU and the University of Tokyo. The success of their work over the past seven years has fostered the desire to continue their relationship in research.

“We are honored to be chosen for this grant. It showcases FIU’s capabilities and also allows our students to work with the top universities in the world,” Chen said.

The project is funded for three years. Doctoral students interested in international research and machine-learning algorithms are encouraged to contact Chen or Luis about additional research opportunities.

Shu-Ching Chen


Steven Luis


Ryosuke Shibasaki, University of Tokyo