In this episode, we will be talking to Dr. Aniruddha Adiga, Lijing Wang, and Ben Hurt about the challenges of forecasting an ongoing epidemic such as COVID-19. In addition to the various statistical and machine learning techniques being used, they discuss the pros and cons of multiple external indicators such as mobility and behavior. 

Aniruddha Adiga is a postdoctoral researcher with the NSSAC Division, Biocomplexity Institute, University of Virginia. His research interests include signal processing, machine learning, data mining, and big data analysis. https://biocomplexity.virginia.edu/person/aniruddha-adiga 

Lijing Wang is a graduate student with the Department of Computer Science and student researcher with NSSAC Division, Biocomplexity Institute, University of Virginia. While her current research focuses on combining causal mechanistic models and deep neural network models for epidemic forecasting, she is also interested in machine learning, deep learning, artificial intelligence, time series analysis, and network science. https://biocomplexity.virginia.edu/person/lijing-wang

Benjamin Hurt is a data scientist with NSSAC Division, Biocomplexity Institute, University of Virginia. His research interests include machine learning, artificial intelligence, forecasting, and financial system analysis. https://biocomplexity.virginia.edu/person/ben-hurt