About this online event:

The Data Science Conference on COVID-19 will showcase open source technology and code used to model and analyze the COVID-19 pandemic and will highlight best practices in replicable and reproducible science. Presentations will explore epidemic models of the virus and the pandemics affect on the economy, transportation, the environment, the society and beyond. This conference will provide an opportunity researchers to have their work reviewed and validated by their peers. In a push to encourage transparency, all presentations will provide a link to the projects source code.

Agenda:

Please see the "Agenda" tab above and navigate to the tentative agenda. Thank you.

Recordings: click here or select the "recordings" button at the top.

Organizing Committee:

Benjamin Ortiz-Ulloa: ben@datacommunitydc.org

Jun Yan: jun.yan@uconn.edu

Mike Jadoo: mike@datacommunitydc.org

Donna LaLonde

Wendy Martinez

DSCC-19 Code of Conduct: Participation/attendance in this event indicates your agreement to abide by our code of conduct policy.

The Journal of Data Science

The Journal of Data Science publishes research works on a wide range of topics that involving understanding and making effective use of field data --- i.e., all aspects of applied statistics. We prefer applied research and emphasis is on the relevance of the underlying problem rather than pure mathematical depth. We prefer papers with solid applications and real cases. Detailed technical proof, particularly those that push to the extreme, is not required. The papers published in the Journal of Data Science will cover a wide range of spectrum, as can be seen from the affiliations of the members of our editorial board. The July 2020 issue is a special issue on "Data Science in Action in Response to the Outbreak of COVID-19"; see a preview of the issue at https://https://jdatasci.netlify.app/2020/.

National Institute of Statistical Science

NISS is a national institute of modest size that delivers high-impact research in science and in public policy by leveraging the rich expertise of its staff with that of its base of affiliated organizations in academia, industry and government. As its name indicates, NISS works on issues where information and quantitative analysis are keys to solutions and decisions.

Department of Statistics at the University of Connecticut

The Department of Statistics at the University of Connecticut was founded in 1962. As one of the major statistics departments in New England, it provides outstanding preparation for careers in academia, industry, or government. With a core faculty of 23 professors whose teaching and research interests span virtually all major statistical specializations, our department has received national and international recognition in graduate education and research. Graduates from UConn have found excellent positions in academics, government, and industry.

Data Community DC

Data Community DC is a non-profit 501(3)(c) organization committed to connecting and promoting the work of data professionals in the National Capital Region by fostering education, opportunity, and professional development through high-quality, community-driven events, resources, products and services.