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COVID-19 resource page for AI researchers

March 24, 2020
Novel Coronavirus SARS-CoV-2 by NIAID-RML. CC-BY-2.0.

Machine learning techniques are already playing a key role in assisting research into COVID-19. Here we provide a living document where we will add links to resources as and when we become aware of them. We hope this will be useful for AI researchers wishing to contribute their expertise to projects and collaborations.

Datasets and code

COVID-19 Open Research Dataset (CORD-19)
An open-source, machine-readable collection of scholarly literature covering COVID-19, SARS-CoV-2, and the Coronavirus group. This free resource contains over 29,000 relevant scholarly articles, including over 13,000 with full text.

Johns Hopkins University dashboard of COVID-19 cases
The data for this resource is on GitHub so others can copy and modify as required.

Database of chest x-rays from University of Montreal
The team are building a database of COVID-19 cases with chest X-ray or CT images. They are looking for COVID-19 cases as well as MERS, SARS, and ARDS.

COVID-19 Korea dataset
This is a comprehensive dataset of all the available data on the disease from Korea.

2019-nCoV / SARS-CoV-2 Genome sequence
Provided by kaggle, where you can also find further links to useful websites.

The COVID-19 Vulnerability Index (CV19 Index)
This repository contains the source code, models, and example usage of the COVID-19 Vulnerability Index (CV19 Index). The CV19 Index is a predictive model that identifies people who are likely to have a heightened vulnerability to severe complications from COVID-19.

COVID-19 tweets
This dataset contains the Tweets of users who have applied the following hashtags: #coronavirus, #coronavirusoutbreak, #coronavirusPandemic, #covid19, #covid_19

Code for modelling estimated deaths and cases for COVID19
This is available on the Imperial College London GitHub page.

Funding for COVID-19 research

The Digital Transformation Institute has issued a call for proposals to receive funding for research into AI techniques to mitigate COVID-19 and future pandemics DTI is a new research consortium established by, Microsoft Corporation, the University of Illinois at Urbana-Champaign (UIUC), the University of California, Berkeley, Princeton University, the University of Chicago, the Massachusetts Institute of Technology, Carnegie Mellon University, and the National Center for Supercomputing Applications at UIUC.

Up to $5.8 million in awards will be funded from this first call, ranging from $100,000 to $500,000 each. In addition to cash awards, DTI recipients will be provided with significant cloud computing, supercomputing, data access, and AI software resources and technical support provided by Microsoft and The first call for proposals is open now, with a deadline of May 1, 2020. You can find out have to submit your proposal here.

Get funding for ideas that address COVID-19 (UK only)
UK Research and Innovation is inviting proposals for short-term projects addressing and mitigating the health, social, economic, cultural and environmental impacts of the COVID-19 outbreak.

Information and review articles

COVID-19 information guide from Gerstein Science Information Centre, University of Toronto Library
This comprehensive set of webpages provides information and news about the virus and resources for researchers

Mapping the landscape of artificial intelligence applications against COVID-19
This arXiv article presents an overview of recent studies using artificial intelligence to tackle many aspects of the COVID-19 crisis at different scales including molecular, medical and epidemiological applications.

Interactive website that gives a ten-day forecast, by country, on likely numbers of COVID-19 cases
This was developed by a team from the University of Melbourne. The code is available here.

Conferences, forums and collaborations

ELLIS against COVID-19 online workshop
Hosted by the ELLIS society, this workshop was held on 1 April 2020 and covered outbreak prediction, epidemiological modelling, drug development, viral and host genome sequencing, and health care management. You can watch the event here

COVID-19 and AI: A Virtual Conference
This event was hosted by the Stanford Institute for Human-Centered Artificial Intelligence, Stanford University and was held on 1 April 2020. Topics addressed included: AI applications in diagnostics and treatment, epidemiological tracking and forecasting of the spread of the virus, information and disinformation, and the broader human impact of COVID-19 and pandemics in general on economies, culture, government, and human behaviour. You can watch the event here.

Join the AI-ROBOTICS vs COVID-19 initiative of the European AI Alliance
The European Commission has launched an initiative to collect ideas about deployable Artificial Intelligence (AI) and Robotics solutions as well as information on other initiatives that could help face the ongoing COVID-19 crisis. The initiative aims to create a unique repository that is easily accessible to all citizens, stakeholders and policymakers and become part of the joint European response to the outbreak of COVID-19. Click here to find out how to submit your ideas.

GOVLAB have created a living repository – add information about your projects
The repository is part of a call for action to build a responsible infrastructure for data-driven pandemic response. It serves as a source for data collaboratives seeking to address the spread of COVID-19 and its secondary effects. is launching a joint task force to bring all players together in response to COVID-19. Email to get involved.

Join Montreal AI on Slack
They team are inviting people to join them to collaborate on matters of importance (including the COVID-19 outbreak).

CLAIRE (Confederation of Laboratories for Artificial Intelligence Research in Europe) offers assistance to governments
You can read their open letter here.
CLAIRE have released their first daily update (24th March) – read it here.

COVID-19 forum hosted by
This is a forum for discussions that are data-driven, technical and/or practical. Share and join projects for building ventilators, finding reagents for testing, improving contact tracing, public policy discussions and communications, etc.

The UK government have called for researchers to provide expertise.
Sign up here.

UK call for modellers to support epidemic modelling
The Royal Society is coordinating a scheme to allow those with modelling skills (including data science) to contribute to current UK efforts in modelling the COVID-19 pandemic. More details, including the online form can be found here.

Call for COVID-19 rapid response data science taskforce
DECOVID is a collaboration between The Alan Turing Institute, HDR UK and founding Trusts and academic partners at University Hospitals Birmingham/University of Birmingham and University College London Hospitals/University College London. DECOVID aims to address urgent questions defined by clinical staff in order to produce rapid insights which are actionable on the frontline at a local level. This is a joint call for teams of researchers as well as individual researchers to join DECOVID in addressing urgent questions. Teams will rapidly trial tested, robust and reproducible data science and machine learning methods on the new national data resource of COVID ICU data, to create a near real-time, human-in-the-loop analytics platform and information console to support acute care management and clinical decision making for COVID-19. The form with detailed information can be found here.

Computing power and resources

Donate some of your computing power to folding@home to help run simulations
Download folding@home and the software runs while you are doing other things.

Get free computing power for COVID-19 research
Rescale, Google Cloud and Microsoft Azure announced a new program that immediately offers high performance computing resources at no cost to teams working on COVID-19.
Sign up here.

Element AI provides a search platform to assist in finding information from research papers
This natural language web platform is designed to help with searches of structured and unstructured information and the initial version has been configured to work with the COVID-19 Open Research Dataset (CORD-19) corpus.

Research tasks, classes and challenges

MIT and J-Clinic announce an open task: fighting secondary effects of COVID-19
The task is to predict a target compound’s property from its molecular structure. You can find out more here. The open datasets can be accessed from the website or from GitHub.

Stanford University are organising a “data science and AI for COVID-19” project class
This starts on 10 April and they plan to make a lot of the information public.

Kaggle COVID-19 challenge
There are 10 tasks for people to work on.
In addition, there are two forecasting challenges:
Global forecasting
Local forecasting for California, USA

If you have any suggestions for resources or links we should add to the page then please get in touch at aihuborg[at]

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