Bringing Data Science to Disaster Response and Disaster Management

Washington, D.C. Campus

GA D.C.
509 7th Street NW, 3rd Floor
Washington D.C. 20004

Bringing Data Science to Disaster Response and Disaster Management

Washington, D.C.

Washington, D.C. Campus

GA D.C.
509 7th Street NW, 3rd Floor
Washington D.C. 20004

About this event

General Assemblys <a href="https://generalassemb.ly/education/data-science-immersive">Data Science Immersive</a> course partnered with New Light Technologies’ industry expertise to train the next generation of data scientists to make better decisions through data. More than 100 students across ten of General Assemblys campuses in the U.S. were challenged to find innovative ways to utilize technology and big data to address some of the most fundamental problems of today's world.

For over 10 years, New Light Technologies Inc. (NLT) has been supporting FEMA prepare for, protect against, respond to, recover from and mitigate various types of hazards. In the last year, NLT has also been supporting the World Bank to better utilize geospatial data to improve the Bank`s understanding about the developing world.

This partnership has resulted in more than 20 innovative student projects that bring together state-of-the-art theories in data science, artificial intelligence, machine learning and open-source data to improve decision-making during disasters. These projects could help save lives and improve how agencies prepare for and respond to disasters. Through their work, these students have developed tools introducing some groundbreaking concepts into the realm of disaster response operations. One tool used live newsfeeds to automatically identify isolated communities requiring immediate search and rescue efforts, for example. Others predicted economic loss and impacts upon citizens of specific events; alerted about new disasters in real-time; or assessed the extent of damage caused to infrastructure with social media photos or images collected by drones. All the tools and codes that were developed by the students are open source and could be deployed as soon as the next disaster occurs.

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