Draft
Modeling the Impact of Social Distancing and Targeted Vaccination on the Spread of COVID-19 Through a Real City-Scale Contact Network
Uses mobile device data to construct empirical interpersonal physical contact networks both before and after social distancing measures during the COVID-19 pandemic and investigates how the epidemic responds when part of the population is vaccinated.
Jul 13, 2021
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Protecting the Most Vulnerable by Vaccinating the Most Active
In this Perspective, the authors used a network model to illustrate five different vaccination strategies for coronavirus disease 2019, showing that vaccinating the most-active people might be the best way to protect the vulnerable in the pandemic.
Feb 15, 2021
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Operationally Relevant Artificial Training for Machine Learning: Improving the Performance of Automated Target Recognition Systems
The authors explore whether an object-detection model trained on artificial images could evaluate real images as an automated target recognition system, an important advancement in artificial intelligence and machine learning for the U.S military.
Nov 18, 2020
Draft
Deep Generative Modeling in Network Science with Applications to Public Policy Research
Explores deep generative modeling in network science towards informing key public policy questions.
Sep 30, 2020
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Maintaining the Competitive Advantage in Artificial Intelligence and Machine Learning
If its current artificial intelligence plan is successful, China will achieve an advantage over the United States and its allies. That has significant strategic implications that the United States must address.
Jul 8, 2020