Aniruddha Adiga is a research scientist in the Network Systems Science and Advanced Computing division. His interests are in signal processing, machine learning, and deep learning, with a current focus on the development of forecasting models. From May 2018 to May 2019, he was a postdoctoral associate at North Carolina State University. He received his Ph.D. from the Department of Electrical Engineering at the Indian Institute of Science in 2018 and worked on sparse representation of signals and the development of blind deconvolution algorithms. Aniruddha has published in top venues such as KDD, AAAI, IJCAI, BigData, etc. His paper in IEEE BigData 22 received the "Best Paper" award. He also supports public health agencies such as CDC, Eu CDC, and VDH with forecasts for multiple diseases.
The model predicts that under conditions of “strong control” the number of statewide cases could instead peak around Jan. 10.
The 2019 Novel Coronavirus (COVID-19), which originated in Wuhan, China, in late 2019, has received significant global attention due to the rapid speed and widespread reach of the outbreak. As of early March 2020, COVID-19 has exceeded 92,000 confirmed cases in 76 countries within a span of two months. In response to this global pandemic, researchers from the University of Virginia’s Biocomplexity Institute have developed a series of visualization and analytical web applications to provide a greater understanding of the pandemic’s scope, and to help officials, healthcare systems, and policy makers worldwide, control and ultimately stop the outbreak.