Berkeley Lab researchers with expertise in lasers and in biology are working together to develop a platform and experiments to study the structure and components of viruses and to learn how they interact with their surrounding environment. The experiments could provide new insight on how to reduce the infectiousness of viruses such as the one causing COVID-19.
Using Machine Learning to Estimate COVID-19’s Seasonal Cycle
A cross-disciplinary team of Berkeley Lab scientists with expertise in climate modeling, data analytics, machine learning, and geospatial analytics is launching a project to determine if the novel coronavirus might be seasonal. The team will apply machine-learning methods to a plethora of health and environmental datasets, combined with high-resolution climate models and seasonal forecasts.
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