COVID Chasers

In this episode, we will be talking to Dr. Alex Telionis, Dr. James Schlitt and Joseph Outten about the various analytics that help understand and respond to outbreaks and epidemics. Especially, they will discuss a few examples of visualizations that were generated to help policymakers during the COVID-19 response. 

Alex Telionis is a postdoctoral researcher with the NSSAC Division, Biocomplexity Institute, University of Virginia. https://biocomplexity.virginia.edu/person/alex-telionis

James Schlitt is a postdoctoral researcher with the NSSAC Division, Biocomplexity Institute, University of Virginia. https://biocomplexity.virginia.edu/person/james-schlitt

Joseph Outten is a final year undergraduate student at University of Virginia, majoring in Computer Science and Biology. His research interests lie in the intersection of these two fields and include topics from biotechnology, synthetic biology, and bioinformatics. Full bio at https://biocomplexity.virginia.edu/person/joseph-outten

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 

In this episode, we will be talking with Mandy Wilson and Dawen Xie about designing and maintaining multiple dashboards that serve epidemiological information to multiple stakeholders. Ranging from disease surveillance to hospital capacity and intervention management, they discuss the trials and tribulations of building these platforms and constantly improving them based on user feedback. 

Mandy Wilson is a research scientist at the NSSAC division, Biocomplexity Institute at the University of Virginia; prior to that, she was an employee of the Biocomplexity Institute of Virginia Tech from 2008 - 2018. Wilson has had a broad range of work experiences, including custom software development for the federal government and the private sector. Her research interests include synthetic biology, modeling behavior on social media, epidemiology, database architecture, and data mining. Full bio at https://biocomplexity.virginia.edu/person/mandy-wilson

Dawen Xie is a research scientist at the NSSAC division, Biocomplexity Institute at the University of Virginia. Xie is interested in the Geographic Information System (GIS), visual analytics, information management system, and database with a current focus on building different dynamic web systems. Full bio at https://biocomplexity.virginia.edu/person/dawen-xie

In this episode, we will be talking to Brian Klahn and Akhil Sai Peddireddy about the challenges of dealing with the constantly shifting data landscape. In addition to describing the how they curated the varied datasets being used by modelers, they talk about the lessons that can be carried forward.

Brian Klahn is a research scientist in the NSSAC division of Biocomplexity Institute, University of Virginia. Klahn served in the U.S. Navy’s Nuclear Power Program, which included active duty in the first Persian Gulf War. Upon honorable discharge, Klahn went on to earn a B.S. in Molecular Biology, followed by an M.S. in Neuro-Physiology from the University of Wisconsin. His research interests include open, robust and maintainable software systems, biological modeling of many kinds and scales, genomic classification and characterization system. Full bio at https://biocomplexity.virginia.edu/person/brian-klahn

Akhil Sai Peddireddy is a Graduate Research Assistant in the NSSAC division of Biocomplexity Institute, University of Virginia. He is pursuing an MS in Computer Science at the University of Virginia. His research interests include global surveillance of epidemics and time-series forecasting of infectious diseases using statistical and machine learning models. Full bio at https://biocomplexity.virginia.edu/person/akhil-peddireddy

In this episode, we talk to Dr. Jiangzhuo Chen about various computational models that have been used by the team to support COVID-19 response. Our co-host, Srini Venkatramanan will also join in describing how these different approaches complement each other.

In this episode we talk to Dr. Bryan Lewis about the challenges associated with communicating about epidemic models and analytics with policymakers and public health departments.  We also discuss how the team has coordinated over the past year for keeping the weekly delivery pipeline up to date and running, while maintaining work-life balance (case in point, Bryan's German Shepard puppy who makes a special appearance!). 

Bryan Lewis is a research associate professor in the NSSAC division, Biocomplexity Institute, University of Virginia. His research interests include public health and epidemiology, epidemic modeling, social network construction, and graph measures and dynamic networks. As a computational epidemiologist, Lewis acts as a liaison between the computer scientists and mathematicians designing and building simulation software and decision makers who want answers to pressing public policy questions. Full bio at https://biocomplexity.virginia.edu/person/bryan-lewis 

In this episode, we talk to Dr. Stephen Eubank and Dr. Madhav Marathe of the Biocomplexity Institute, University of Virginia about aspects of team science and cultivating a trans-disciplinary research environment. We also discuss the team's origins and how it has evolved over the years, rising up to the challenges of supporting pandemic response in real-time. 

Dr. Stephen Eubank is deputy director in the Network Systems Science and Advanced Computing division and a tenured professor, Department of Public Health Sciences, University of Virginia. His research interests include simulating large socio-technical systems, computational epidemiology, scaling in complex systems, and network structure and graph theory. Full bio at https://biocomplexity.virginia.edu/person/stephen-eubank 

Dr. Madhav Marathe is an endowed Distinguished Professor in Biocomplexity, Director of the Network Systems Science and Advanced Computing (NSSAC) Division, and a tenured Professor of Computer Science at the University of Virginia. His research interests include science of massively interacting networked systems, machine learning and artificial intelligence, computational modeling and simulation, and theoretical computer science. Full bio at https://biocomplexity.virginia.edu/person/madhav-marathe

A special podcast series from researchers at the Biocomplexity Institute (NSSAC Division), University of Virginia on supporting COVID-19 response in the United States over the past year. In this episode, the hosts discuss the motivation behind the podcast series, and why it is important to do it in the current, hopefully final, phase of the pandemic.

Hosts: Srini Venkatramanan and Erin Raymond.

Email us at [email protected] or tweet us at @UVA_NSSAC with the hashtag #COVIDChasers.

Additional Notes:

Biocomplexity Institute COVID-19 response: https://biocomplexity.virginia.edu/project/covid-19-pandemic-response

Network Systems Science and Advanced Computing Division: http://biocomplexity.virginia.edu/nssac