UMD Transportation Institute Covid Dashboard

Computer & Data Science

USM institutions are applying world-class expertise in computer science, data science, and information technology to develop leading-edge tools to monitor and analyze the impact of COVID-19.



Researchers are developing data analytics tools to study movement behaviors and provide decision support for policies regarding human mobility restriction, self-quarantine, and mandatory quarantine policies.
In partnership with Facebook, researchers designed survey methodology that will be used to gather data about the spread of COVID-19 from Facebook users worldwide. Other University of Maryland departments will collaborate to integrate the survey results with data visualization tools.
Researchers are working to develop more accurate forecasting models to shed light on the effectiveness of measures taken to contain COVID-19 outbreaks. By using well-established models to study infection data, the team hopes to identify a model that can be used to predict the dynamics of COVID-19.
University of Maryland computing experts are partnering with scientists nationwide on the Global Pervasive Computational Epidemiology project, a National Science Foundation-funded study. As part of the project, UMD faculty will lead development of new machine learning algorithms that can interpret large amounts of data from multiple sources over multiple networks.
The Salisbury University -affiliated Eastern Shore Regional GIS Cooperative has partnered with Peninsula Regional Medical Center to create an online dashboard with information on the number of ventilators in the Maryland/Washington D.C. area in reserve, the number of patients currently intubated and more. The dashboard will assist decision-makers with resource distribution as the pandemic continues.

Maryland Blended Reality Center

University of Maryland, College Park

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Point-of-care ultrasound (POCUS) is emerging as an important diagnostic tool for COVID-19 patients. The Maryland Blended Reality Center is developing new artificial intelligence (AI) tools that will analyze and display POCUS images quickly, accurately, and in a way designed to facilitate clinical decision-making. The technology will allow quantification and standardization of lung and cardiac ultrasound findings in COVID-19, which is not currently possible.
Rita Colwell, Distinguished University Professor, University of Maryland Institute for Advanced Computer Studies, developed a model to predict when and where the next flare-up of COVID-19 cases will occur. Colwell applied machine learning to global data to extract correlations with data gathered from satellites, as well as air temperatures and surface parameters of moisture, such as humidity and dew point.
A team of researchers has developed a novel news and tweet aggregating web application that is able to track the progression of COVID-19 over space and time. The web application, called NewsStand CoronaViz is a prototype that enables dynamic map visualizations of COVID-19 variables, such as current number of infection or recoveries. This information is then bolstered by any reference to COVID-19 in news articles and tweets as they occur in real time.

Robert H. Smith School of Business

University of Maryland, College Park

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Professor Louiqa Raschid, a data science and data management expert has received funding from the National Science Foundation to improve supply chain networks used for critically needed medical equipment during the COVID-19 crisis. The project will harness data from a diverse set of sources and develop machine learning approaches to predict supply chain relationships.

University of Maryland, College Park

University of Maryland, College Park

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Professor Philip Resnik, a computational linguistics expert, has received funding from the National Science Foundation (NSF) to develop advanced topic modeling methods that can quickly and effectively analyze text responses in COVID-19 survey data. Resnik will lead a team that will address the problem of analyzing unstructured language in open-ended responses, which is currently a labor-intensive process.
Faculty in the Geometric Algorithms for Modeling, Motion, and Animation (GAMMA) research group have received a National Science Foundation grant to develop robotic systems able to assist humans in maintaining social distancing guidelines. The project is exploring new methods that leverage machine learning, computer vision, and robot motion planning to identify the positions of pedestrians as they move in a confined area.

Department of Information Systems (UMBC) & School of Medicine (UMB)

University of Maryland, Baltimore County
University of Maryland, Baltimore

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A research team from UMBC and the University of Maryland School of Medicine has received a National Science Foundation grant to use machine learning to improve the speed and accuracy of COVID-19 diagnosis. Aryya Gangopadhyay, UMBC professor of information systems, is the principal investigator on the grant. His team will design, build, and train deep neural networks to detect cases of COVID-19.
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USM Experts and Institutions

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USM experts seek opportunities to collaborate on solutions to the COVID-19 crisis. Now more than ever, partnership is critical.
To make a connection, use the contact form or email covidsolutions@usmd.edu.

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