{"id":9130,"date":"2020-10-29T13:55:36","date_gmt":"2020-10-29T17:55:36","guid":{"rendered":"https:\/\/dcp.ufl.edu\/urp\/?p=9130"},"modified":"2020-11-07T10:28:58","modified_gmt":"2020-11-07T15:28:58","slug":"microsoft-ai-for-earth-grant","status":"publish","type":"post","link":"https:\/\/dcp.ufl.edu\/urp\/microsoft-ai-for-earth-grant\/","title":{"rendered":"Microsoft AI for Earth Grant"},"content":{"rendered":"\n
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Microsoft AI for Earth Grant<\/em><\/h1>
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A team led by URP doctoral candidate Wei Zhai and Professor Zhong-Ren Peng received a prestigious Microsoft grant to understand human mobility during extreme weather events.<\/p><\/div>\n<\/div><\/div>\n\n\n\n

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AI for Earth<\/a> is a global US$50 million Microsoft research grant program aimed at “tackling some of the world\u2019s most intractable problems by marshaling the immense power of AI, machine learning (ML), and the cloud.” Image source: Microsoft.<\/p>\n\n\n\n

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October 29, 2020<\/h6>
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URP doctoral candidate Wei Zhai<\/strong> and Dr. Zhong-Ren Peng<\/strong>, together with Ph.D. students Hongming Li <\/strong>and Mengdi Zhu<\/strong> from the UF Department of Electrical and Computer Engineering, won an AI for Earth Grant from Microsoft<\/a>. AI for Earth awards grants internationally to support projects that use AI to change the way people and organizations monitor, model, and manage Earth\u2019s natural systems.<\/p>\n\n\n\n

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Members of the grant team (from left): Wei Zhai (Urban and Regional Planning), and Mengdi Zhu and Hongming Li (Electrical and Computer Engineering)<\/figcaption><\/figure>\n\n\n\n

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The grant project will automatically uncover the major weather-related features that impact human mobility during extreme weather events (EWEs) in big cities by mining mobile phone data and weather data. In addition, the project also aims to build an effective model to predict human mobility during EWEs using the AI-based approach, such as the Sequential Deep Learning models.<\/p>\n\n\n\n

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An example “extreme weather event,” flooding in Houston from Hurricane Harvey, 2017. Source: Lt. Zachary West, Army National Guard\/Getty Images<\/figcaption><\/figure>\n\n\n\n

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This project would not only benefit existing scholarship, but also the work of thousands of practitioners that are monitoring and responding to the emergency evacuation, traffic congestion, disaster response, and long-term impacts during EWEs. The project will develop a real-time online platform to predict the people\u2019s mobility patterns given the real-time input of extreme weather data for America\u2019s big cities. The research team will work with university research institutions, NGOs, and communities to build a real-time monitoring system. The team will disseminate the results to all big cities (e.g., New York City, Los Angeles) and local disaster management agencies (e.g., Florida Division of Emergency Management), which will help decision-makers and emergency respondents to make real-time decisions and  immediate adaptation strategies during EWEs.<\/p>\n\n\n\n

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A team led by URP doctoral candidate Wei Zhai and Professor Zhong-Ren Peng received a prestigious Microsoft grant to understand human mobility during extreme weather events.<\/p>\n","category_list_v2":"Doctoral students<\/a>, Institutes, Centers and Programs<\/a>, International Center for Adaptation Planning and Design (iAdapt)<\/a>, Research<\/a>, Students<\/a>","author_info_v2":{"name":"kifrank","url":"https:\/\/dcp.ufl.edu\/urp\/author\/kifrank\/"},"comments_num_v2":"0 comments","uagb_featured_image_src":{"full":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1.jpg",968,800,false],"thumbnail":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1-150x150.jpg",150,150,true],"medium":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1-300x248.jpg",300,248,true],"medium_large":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1-768x635.jpg",768,635,true],"large":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1.jpg",968,800,false],"1536x1536":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1.jpg",968,800,false],"2048x2048":["https:\/\/dcp.ufl.edu\/urp\/wp-content\/uploads\/sites\/34\/2020\/10\/sunrise-1756274_1920-1600x800-2-1.jpg",968,800,false]},"uagb_author_info":{"display_name":"kifrank","author_link":"https:\/\/dcp.ufl.edu\/urp\/author\/kifrank\/"},"uagb_comment_info":0,"uagb_excerpt":"A team led by URP doctoral candidate Wei Zhai and Professor Zhong-Ren Peng received a prestigious Microsoft grant to understand human mobility during extreme weather events.","_links":{"self":[{"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/posts\/9130","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/users\/136"}],"replies":[{"embeddable":true,"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/comments?post=9130"}],"version-history":[{"count":0,"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/posts\/9130\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/media\/9244"}],"wp:attachment":[{"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/media?parent=9130"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/categories?post=9130"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dcp.ufl.edu\/urp\/wp-json\/wp\/v2\/tags?post=9130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}