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COVID-19 Symposium Day 2
Andrew Beam · Tristan Naumann · Katherine Heller · Elaine Nsoesie

Wed Dec 09 12:00 PM -- 04:00 PM (PST) @ None

The COVID-19 global pandemic has disrupted nearly all aspects of modern life. This year NeurIPS will host a symposium on COVID-19 to frame challenges and opportunities for the machine learning community and to foster a frank discussion on the role of machine learning. A central focus of this symposium will be clearly outlining key areas where machine learning is and is not likely to make a substantive impact. The one-day event will feature talks from leading epidemiologists, biotech leaders, policy makers, and global health experts. Attendees of this symposium will gain a deeper understanding of the current state of the COVID-19 pandemic, challenges and limitations for current machine learning capabilities, how machine learning is accelerating COVID-19 vaccine development, and possible ways machine learning may aid in the present and future pandemics.

Wed 12:00 p.m. - 12:15 p.m.
Opening remarks for day 2 of COVID-19 Symposium (Introduction to day 2)
Wed 12:15 p.m. - 12:50 p.m.
AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19 (Invited Talk)   
Aisha Walcott-Bryant
Wed 12:50 p.m. - 1:00 p.m.
Walcott-Bryant Q&A
Aisha Walcott-Bryant
Wed 1:00 p.m. - 1:35 p.m.
Bayesian nowcasting of COVID-19 regional test results in England (Invited talk)   
Chris C Holmes
Wed 1:35 p.m. - 1:45 p.m.
Chris Holmes Q&A (Q&A)
Chris C Holmes
Wed 1:45 p.m. - 2:20 p.m.
Moderna, Vaccine Science, and a Health Information Revolution (Invited talk)
Noubar Afeyan
Wed 2:20 p.m. - 2:30 p.m.
Break (Q&A)
Wed 2:30 p.m. - 2:34 p.m.
Transfer Learning with Neural Motif Transformer for Predicting Protein-Protein Interactions Between SARS-CoV-2 and Humans (Spotlight)   
Jack Lanchantin
Wed 2:34 p.m. - 2:38 p.m.
Addressing Public Health Literacy Disparities through Machine Learning: A Human in the Loop Augmented Intelligence based Tool for Public Health (Spotlight)   
Anjana Susarla
Wed 2:38 p.m. - 2:42 p.m.
Quantifying Uncertainty in Deep Spatiotemporal Forecasting for COVID-19 (Spotlight)   
Yi-An Ma, Rose Yu
Wed 2:42 p.m. - 2:46 p.m.
Mobility network models of COVID-19 explain inequities and inform reopening (Spotlight)   
Serina Chang
Wed 2:46 p.m. - 2:50 p.m.
Unsupervised learning for economic risk evaluation in the context of Covid-19 pandemic (Spotlight)   
Wed 2:50 p.m. - 2:54 p.m.
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds (Spotlight)   
Erik Drysdale
Wed 2:54 p.m. - 2:58 p.m.
Using Wearables for Influenza-Like Illness Detection: The importance of design (Spotlight)   
Bret Nestor
Wed 2:58 p.m. - 3:02 p.m.
A Bayesian Hierarchical Network for Combining Heterogeneous Data Sources in Medical Diagnoses (Spotlight)   
Claire Donnat
Wed 3:02 p.m. - 3:06 p.m.
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning (Spotlight)   
Marcin Skwark
Wed 3:06 p.m. - 3:10 p.m.
Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Signature of Disease (Spotlight)   
Manik Kuchroo

Author Information

Andrew Beam (Harvard)
Tristan Naumann (Microsoft Research)
Katherine Heller (Duke)
Elaine Nsoesie (Boston University School of Medecine)

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