Welcome and Introduction
Presentation: Pandemic Monitoring and Surveillance using AI
Presentation: Scaling Up Health Care and Public Health
Simon de Montigny - Assistant Professor - University of Montreal
Scaling Up Health Care and Public Health
The COVID-19 pandemic shows the need for increasing the intensive care capacity of hospitals as well as the responsiveness of public health services. Artificial intelligence could help health workers handle more patients and more data efficiently. In this webinar, I will present some of my research projects that have implications for pandemic preparedness and response.
Simon de Montigny holds a PhD in mathematics from Polytechnique Montreal. He is currently Assistant Research Professor at the Department of Social and Preventive Medicine at the University of Montreal's School of Public Health and Researcher at the CHU Sainte-Justine Research Center. His research program focuses on artificial intelligence and big data applied to precision medicine and precision public health.
Presentation: Data-efficient Deep Learning to Better Model Emerging Biology
Sébastien Giguère - Co-Founder - InVivo AI
Data-efficient Deep Learning to Better Model Emerging Biology
The COVID-19 outbreak offers a solemn reminder of how little we know - and how little data we have - for emerging biology. Novel, data-efficient learning algorithms are needed for these types of data poor environments. InVivo AI is developing novel algorithms capable of learning from small and noisy biological datasets. In light of the COVID-19 outbreak, the startup is leveraging their platform to learn models for the discovery of novel drug and vaccine therapies. In this webinar, we will present some of the opportunities for AI to contribute to finding therapeutic solutions to the current and future pandemics.
Expert in machine learning and computational biology passionate about bridging the gap between the computational and life sciences. Before co-founding InVivo AI, Dr. Giguère has spent significant amounts of time working with research laboratories, pharmaceutical companies and hospital networks on projects including the use of machine learning for design of pharmaceutical compounds, the prediction of antigen recognition by the MHC pathway for vaccine and immunotherapy development, the prediction of protein-protein interactions and kinase phosphorylation for drug target identification, and the prediction of antimicrobial resistance for the treatment of multi-drug resistant infection.
Q&A with the Speakers
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