We encourage submission of original research relevant to mitigating the impact of COVID-19. Examples of impactful use cases include:
- GNNs for drug design
- GNNs for drug repurposing and treatment design
- GNN-powered epidemiological forecasting models
- GNN-based supply chain demand forecasting
All submissions will be considered for a virtual poster presentation at the workshop and up to three will be selected for a COVID-19-specific contributed talk. For more detaills on submitting, please consult our Call for Papers. All submissions are strongly encouraged to discuss the ethical aspects of their use case, data, and methodology.
Mission AI Cures provides a suite of machine learning tasks with corresponding datasets to which everyone can contribute. We welcome submissions that showcase methodology and results on these tasks.
For an overview of how graph representation learning methods can be used in the fight against COVID-19, please see the following slide deck: Graph Methods for COVID-19 Response, prepared by William L. Hamilton (McGill University/Mila).
Other data resources include but are not limited to:
- Coronavirus Disease (COVID-19) – Statistics and Research
- COVID-19 Open Research Dataset Challenge (CORD-19)
- Individual case data for Singapore, India, Brazil, and Switzerland
- The COVID Tracking Project in the US
- Mobility data for Italy
- Citymapper Mobility Index
- COVID-19 data from Johns Hopkins Center for Systems Science and Engineering
- NYC COVID-19 data
- COVID-19: The Public Coronavirus Twitter Dataset
- Face-to-face contact datasets