Fourteen AI research projects join the fight against COVID-19

Projects include machine learning research and applications to identify potential treatments, to support public health measures such as social distancing, and to better understand the viral transmission of COVID-19.

Fourteen new AI research projects will be launched to address the COVID-19 outbreak through CIFAR’s AI and COVID-19 Catalyst Grants initiative.

The projects will be complete in as early as three months to one year, exploring a range of topics that use AI to:

• Use medical imaging and AI to predict how sick someone will become following COVID-19 infection and understand which existing drugs may be effective in treating COVID-19

• Understand how the virus is mutating as it is transmitted through the population

• Identify at-risk populations and predict disease course, both at individual and population-wide levels, to understand the transmission of COVID-19 in children and their families

• Understand the mental health impacts of the COVID-19 outbreak through social media analysis

CIFAR’s AI and COVID-19 Catalyst Grants Program is funded by the Ontario Government, Microsoft Research, the Natural Sciences and Engineering Research Council of Canada (NSERC), Genome Canada,the Max Bell Foundation and many individual donors. Launched on March 23, 2020, the program funds innovative, high-risk, high-reward ideas and projects that address the current COVID-19 outbreak.

Successful AI and COVID-19 Catalyst Grant recipients:

• PanXcea: PANdemic Prediction with X-ray-based COVID-19 External Analysis
  Collaborators: Marzyeh Ghassemi (Canada CIFAR AI Chair, Vector Institute, University of Toronto), Joseph Paul Cohen (Mila, Université de Montréal), Chris McIntosh (University of Toronto)
• COVIDEX – Advanced Information Retrieval for Clinical and Academic Literatures
  Collaborators: Kyunghyun Cho (CIFAR fellow,  Learning in Machines & Brains program, New York University),  Jimmy Lin (Vector Institute, University of Waterloo)
• Leveraging Biomedical Knowledge Graphs for COVID-19 Drug Repurposing Strategies
  Collaborators: Jian Tang (Canada CIFAR AI Chair, Mila, HEC Montréal), William L. Hamilton (Canada CIFAR AI Chair, Mila, McGill University), Yoshua Bengio (Canada CIFAR AI Chair and co-director, CIFAR Learning in Machines & Brains program, Mila, Université de Montréal), Guy Wolf (Mila, Université de Montréal), Yue Li (Mila, McGill University)
• COVID-Net: An Open Source Deep Learning Platform for COVID-19 Detection and Risk Stratification
  Collaborators: Alexander Wong (University of Waterloo), James Lee, Linda Wang, and Desmond Lin (University of Waterloo)
• Rapid, Automated Assembly of SARS-CoV-2 Phylogenies
  Collaborators: Quaid Morris (Canada CIFAR AI Chair, Vector Institute, University of Toronto), Jeffrey Wintersinger (University of Toronto), Jeff Wrana and Ben Blencowe
• Modeling the Transmission of SARS-CoV-2 Between Zoonotic Sources on a Gene Level
  Collaborators: Guillaume Rabusseau (Canada CIFAR AI Chair, Mila, Université de Montréal), Vladimir Makarenkov (Université du Québec à Montréal), Bogdan Mazoure (Mila, McGill University)
  • This project includes funding from Genome Canada
• MyTrace / MaTrace: A Privacy-Compliant Contact-Tracing Mobile App for COVID-19
  Collaborators: Alán Aspuru-Guzik (Canada CIFAR AI Chair, CIFAR fellow, Bio-Inspired Solar Energy program, Vector Institute), Maryzeh Ghassemi (Canada CIFAR AI Chair, Vector Institute, University of Toronto)
• Machine Learning Against COVID-19: Accelerating Small Molecule Drug Discovery
  Collaborators: Sarath Chandar (Canada CIFAR AI Chair, Mila, Polytechnique Montréal), Matthew Taylor (Amii, University of Alberta), Sai Krishna (99andBeyond), Karam Thomas (99andBeyond)
• Guarding At-Risk Demographics with AI (GuARD-AI)
  Collaborators: Daniel C. Baumgart (University of Alberta), Martha White (Canada CIFAR AI Chair, University of Alberta, Amii), Randy Goebel (Amii, University of Alberta), Robert Hayward (Chief Medical Information Officer, Alberta Health Services), Shy Amlani, (Virtual Health), Jonathan Choy (Virtual Health), Sara Webster (Virtual Health), and Sarah Hall (Virtual Health)
• Detecting and Monitoring Pneumonia in COVID-19 Patients Using Machine Learning and Ultrasound Imaging
  Collaborators: Kumaradevan Punithakumar (University of Alberta), Russell Greiner (University of Alberta, Amii), Jacob Jaremko (University of Alberta), Nathaniel Meuser-Herr (Upstate Health Care Center, NY), Dornoosh Zonoobi (MEDO.ai)
• AI-Driven Identification and Validation of Drug Repurposing Candidates to Treat COVID-19
  Collaborators: Jean-Philippe Julien (CIFAR fellow, Molecular Architecture of Life program, University of Toronto), Costin Antonescu (Ryerson University), Cyclica Inc. (industry partner), Phoenox Pharma (industry partner)
• Preventing COVID-19 Infection in Families: The COVID-19 Child and Family Study
  Collaborators: Jonathon Maguire (Hospital for Sick Children), Anna Goldenberg (Canada CIFAR AI Chair and CIFAR fellow, Child and Brain Development program, Vector Institute, University of Toronto, Hospital for Sick Children), Marzyeh Ghassemi (Canada CIFAR AI Chair, Vector Institute, University of Toronto), Catherine Birken (Hospital for Sick Children), Peter Jüni (St. Michael’s Hospital) Kevin Thorpe (Sunnybrook Hospital), Charles Keown-Stoneman (St. Michael’s Hospital), Mary Aglipay (St. Michael’s Hospital)
• Tracking Mental Health During the Coronavirus Pandemic
  Collaborators: Alona Fyshe (Canada CIFAR AI Chair, CIFAR Learning in Machines & Brains program, Amii, University of Alberta), Daniel Lizotte (Western University), Rumi Chunara (New York University)
• Planning as Inference in Epidemiological Dynamics Models
  Collaborators: Frank Wood (Canada CIFAR AI Chair, Mila, University of British Columbia), Benjamin Bloem-Reddy, Alexandre Bouchard, Trevor Campbell (University of British Columbia)

Words from our funders

• “Our government is exploring every opportunity including critical AI research to combat COVID-19 and to contribute to the worldwide knowledge base on this virus,” says Ross Romano, Ontario Minister of Colleges and Universities. “This new virus requires innovative ways of thinking and solving problems. Our investment will help fund the necessary equipment and lab space to make this AI research possible.”
• “The scale and size of the current global pandemic requires a collaborative approach between industry, non-profits, governments, researchers, and clinicians,” says John Kahan, Microsoft’s chief data analytics officer and Global AI for Health lead. “We’re proud to partner with CIFAR to support the AI and COVID-19 Catalyst Grants Program in the acceleration of COVID-19 related research leveraging our Azure High Performance Computing solutions and Azure compute resources and Data Science team.”
• “These grants represent a critical opportunity for interdisciplinary researchers to collaborate on solutions that will support Canadians in their return to everyday life,” says Dr. Alejandro Adem, president, Natural Sciences and Engineering Research Council of Canada. “We are thrilled to partner with CIFAR on this forward-thinking initiative.”
• “Genomics allows us to see how the virus works at the molecular level, and today we are able to accumulate sequencing data on a virus such as COVID-19 faster than ever before. The application of AI computational techniques to this data unlocks a new and much deeper understanding of these enormous genomic datasets and opens up tremendous possibility. The projects in the CIFAR AI and COVID-19 Catalyst Grants program initiative are exciting because they demonstrate the transformative impact genomics is starting to have – and will continue to have – on the health care front,” says Dr. Rob Annan, president and CEO, Genome Canada.
• “The COVID-19 pandemic has called on all of us to contribute what we can to respond to the crisis and work toward recovery,” says Allan Northcott, president, Max Bell Foundation. “CIFAR has been quick to bring its tremendous research and convening capacity to bear on several fronts, including the launch of its catalyst grants program. Max Bell Foundation is pleased to help support their critically important efforts.”