Wei Wang, the Leonard Kleinrock Professor of Computer Science in the UCLA Samueli School of Engineering, has received a one-year, $90,000 rapid-response research grant  from the National Science Foundation to develop a prediction model for the spread of COVID-19.

With the goal of expanding the current epidemiological models, Wang and her research group plan to incorporate a diverse set of data sources in order to comprehensively trace the spread of COVID-19, identify and monitor risk factors, and evaluate the effectiveness of long-term intervention strategies. The model gathers and consolidates data from the news, census, research publications, social media, and outbreak observation trackers.

The researchers will use machine-learning models to map the disease’s spread with individual events, behaviors, activities, and interventions.

By expediting the ability to synchronously track the spread of the virus across geographic locations in the United States, the model can develop place-specific predictions and dynamically monitor risk factors and effective intervention mechanisms. The models and the associated source codes will be made available to the public, providing crucial access to the tools needed to combat the spread of COVID-19.

Wang is the founding director of the Scalable Analytics Institute. She specializes in data mining, data analytics, bioinformatics, and computational biology.

The Information and Intelligent Systems Division under the Directorate for Computer and Information Science and Engineering of NSF funds the award.

 UCLA Samueli Materials Science and Engineering

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