Making data-informed Covid-19 testing plans
A new web-friendly modeling tool helps organizations build tailored Covid-19 testing strategies that can save money and reduce coronavirus spread.
A new web-friendly modeling tool helps organizations build tailored Covid-19 testing strategies that can save money and reduce coronavirus spread.
In a new book, “Data Action,” Associate Professor Sarah Williams issues a call for thinking ethically about data today.
Analysis points to ways engineering strategies could be reimagined to minimize delays and other unanticipated expenses.
Graduate student Manon Revel uses quantitative methodologies to investigate how advertising in online publications affects trust in journalism.
Eaman Jahani examines how resources are distributed across networks as a social and engineering systems PhD student at the Institute for Data, Systems, and Society.
United under the Sustainability Incubator Fund, researchers strategize sustainable sourcing solution for crises at the local and global level.
Letting an algorithm decide which maintenance holes to test for evidence of coronavirus could improve pandemic containment efforts.
Political science professor will spearhead the Institute’s interdisciplinary center that studies high-impact, complex societal challenges.
Researchers urge a holistic approach to forecasting the virus’ impact on public health and the economy.
A new model suggests a plan to keep Covid-19 within the capacity of the health-care system while reopening economic activities.
Media Lab researcher Kate Turner explores how critical race theory can influence science — and how science can inform policy — as an IDSS Research to Policy Engagement Initiative Fellow.
IAIFI will advance physics knowledge — from the smallest building blocks of nature to the largest structures in the universe — and galvanize AI research innovation.
Topics include Covid-19 and urban mobility, strategies for electric vehicle charging networks, and infrastructure and economics for hydrogen-fueled transportation.
Analysis shows requiring masks for public-facing U.S. business employees on April 1 would have saved tens of thousands of lives.
Machine learning system from MIT CSAIL can look at chest X-rays to diagnose pneumonia — and also knows when to defer to a radiologist.