Accepted Papers & Schedule

Contributed Talks (Each awarded a Best Paper for full length contribution)

Physics-based vs. Data-driven: A Benchmark Study on COVID-19 Forecasting

Rui Wang (UC San Diego)*; Danielle Maddix (Amazon Research ); Christos Faloutsos (Amazon Research); Yuyang Wang (Amazon); Rose Yu (UC San Diego)

Detection of Malaria Vector Breeding Habitats using Topographic Models

Aishwarya N Jadhav (Veermata Jijabai Technological Institute)*

FireNet --- Dense Forecasting of Wildfire Smoke Particulate Matter Using Sparsity Invariant Convolutional Neural Networks

Renhao Wang (University of British Columbia)*

Unsupervised Discovery of Subgroups with Anomalous Maternal and Neonatal Outcomes with WHO's Safe Childbirth Checklist as Intervention

Girmaw Abebe Tadesse (IBM)*; William Ogallo (IBM Research); Skyler D Speakman (IBM Research); Aisha Walcott-Bryant (IBM Research - Africa)

(Best Lightning Papers)

Predicting air pollution spatial variation with street-level imagery

Esra Suel (Imperial College London)*; Meytar Sorek-Hamer (USRA at NASA Ames Research Center); Izabela Moise (ETH Zurich); Michael von Pohle (USRA at NASA Ames Research Center); Adwait Sahasrabhojanee (USRA/NASA Ames); Ata Asanjian (NASA); Emily Deardorff (USRA at NASA Ames Research Center ); Violet Lingenfelter (USRA at NASA Ames Research Center ); Nikunj Oza (NASA Ames); Majid Ezzati (Imperial College London); Michael Brauer (University of British Columbia)

Incorporating Healthcare Motivated Constraints in Restless Bandit Based Resource Allocation

Aviva Prins (University of Maryland, College Park)*; Aditya S Mate (Harvard University); Jackson Killian (Harvard University); Rediet Abebe (Harvard University); Milind Tambe (Harvard University)

Addressing Public Health Literacy Disparities through Machine Learning: A Human in the Loop Augmented Intelligence based Tool for Public Health

Xiao Liu (Arizona State University); Anjana Susarla (Michigan State University)*; Rema Padman (Carnegie Mellon University)

Lightning talks:

Twitter Detects Who is Social Distancing During COVID-19

Paiheng Xu (Johns Hopkins University)*; David Broniatowski (George Washington University); Mark Dredze (Johns Hopkins University)

Sequential Stochastic Network Structure Optimization With Applications To Addressing Canada's Obesity Epidemic

Nicholas A Johnson (Massachusetts Institute of Technology)*

How the COVID-19 Community Vulnerability Index and machine learning can enable a precision public health response to the pandemic

Nicholas Stewart (Surgo Ventures); Peter Smittenaar (Surgo Ventures); Staci Sutermaster (Surgo Ventures); Mokshada Jain (Surgo Ventures); Yael Caplan (Surgo Ventures);

Sema K Sgaier (Surgo Ventures)*

Automated Medical Assistance: Attention Based Consultation System

Raj Ratn Pranesh (Birla Institute of Technology, Mesra)*; Ambesh Shekhar (BIT Mesra); Sumit Kumar (Birla Institute of Technology, Mesra)

Scalable Gaussian Process Regression Via Median Posterior Inference for Estimating Multi-Pollutant Mixture Health Effects

Aaron M Sonabend (Harvard University)*; Brent Coull (Harvard University); Jiangshan Zhang (Harvard School of Public Health - Boston, MA); Joel Schwartz (Harvard School of Public Health - Boston, MA); Junwei Lu ()

Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19

Alexander D Rodriguez (Georgia Institute of Technology)*; Nikhil Muralidhar (Virginia Tech); Bijaya Adhikari (University of Iowa); Anika Tabassum (Virginia tech); Naren Ramakrishnan (Virginia Tech); B. Aditya Prakash (Georgia Institute of Technology)

Temporal Graph Analysis for Outbreak Pattern Detection in COVID-19 Contact Tracing Networks

Dario Antweiler (Fraunhofer IAIS)*; Pascal Welke (University of Bonn)

Detecting Individuals with Depressive Disorder from Personal Google Search and YouTube History Logs

Boyu Zhang (University of Rochester)*; Anis Zaman (University of Rochester); Rupam Acharyya (University of Rochester); Ehsan Hoque (University of Rochester); Vincent Silenzio (Rutgers University); Henry Kautz (University of Rochester)

A Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System

Chance Haycock (Alan Turing Institute), Edward Thorpe-Woods (Alan Turing Institute), James Walsh (Alan Turing Institute), Patrick O'Hara (Alan Turing Institute), Oscar Giles (Alan Turing Institute), Neil Dhir (Alan Turing Institute)*, Theo Damoulas (Alan Turing Institute)

Given the NeurIPS 2020 format, all scheduled events will be online. The full schedule with timings is posted here.

Best papers awarded according to review comments and reviewer nominations during the review process.