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)