Archived articles


A united front
Published Summer 2020
Members of the Johns Hopkins community develop tools to tackle COVID-19 / Johns Hopkins Magazine
JHU researcher will build new tools to model pandemic's spread
Published June 12, 2020
Civil and systems engineer Lauren Gardner, whose COVID-19 global tracker is now world famous, will help construct databases to better understand how the coronavirus moves from person to person
Cash transfers to the poor linked to ecological benefits
Published June 12, 2020
Study finds that cash infusions to poor communities in Indonesia led to less deforestation of the nation's rainforests
Building a more secure smart home
Published June 12, 2020
Computer scientist Avi Rubin will work with a national team to develop more secure devices and recommendations for policymakers, companies, and consumers to better protect privacy
Earth science
Big data approach can help map what's beneath the Earth's surface
Published June 12, 2020
Like the explorers who drew the first incomplete maps of America, scientists are using big data approaches to chart the Earth's interior
SARS-CoV-2 is mutating slowly, and that's a good thing
Published June 10, 2020
Johns Hopkins scientists studying the virus that causes COVID-19 say the pathogen has few variations, a promising observation that boosts the chances of developing an effective vaccine
Testing the objectivity of vision
Published June 8, 2020
Johns Hopkins University researchers who study the mind and brain used methods from cognitive science to test a long-standing philosophical question: Can people see the world objectively?
Basic science study may help stop harmful viruses in their tracks
Published June 4, 2020
Johns Hopkins biophysicist Stephen Fried will study the virus that causes COVID-19 and look for ways to block an important mechanism relating to viral replication
Under pressure
Published June 3, 2020
Inspired by colorful coral reefs, Hopkins researchers have created a self-adapting material that can change its stiffness in response to applied force
Radiologists use deep learning to find signs of COVID-19 in chest X-rays
Published June 1, 2020
Despite a shortage of available chest X-rays for patients with COVID-19, the team's model correctly identified the infection 89% of the time