News
Model paves way for faster, more efficient translations of more languages
IDSS affiliate Tommi Jaakkola and CSAIL researchers have developed a model leveraging a metric in statistics, called Gromov-Wasserstein distance, that could lead to faster, more efficient language translations.
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Celebrating the legacy of Michael Hammer and the new Hammer Fellowship
MIT senior leaders and IDSS faculty, staff, and students joined Phyllis Thurm Hammer and her family and friends in a celebration marking the launch of the new Hammer Society of Fellows.
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How should autonomous vehicles be programmed?
A new survey developed by MIT researchers, including Media Lab professor and IDSS affiliate Iyad Rahwan, reveals global preferences and regional variations concerning the ethics of autonomous vehicles. Their paper, “The Moral Machine Experiment,” has been published in Nature.
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Truth, lies, and tribal voters
A look at recent insights about fake news from MIT researchers, including IDSS affiliates Adam Berinksy, Sinan Aral, David Rand, and Teppei Yamamoto.
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HUBweek Policy Hackathon delivers solutions to local challenges
Citizens and data scientists produce actionable recommendations for high-priority Boston-area issues at an IDSS student-run event during Boston's annual ideas festival.
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Refining the “science” of political science
IDSS affiliate Teppei Yamamoto studies political cause and effect, including a project with fellow IDSS affiliate Adam Berinsky examining the effects of news media on political views.
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Tracking how mobile banking and texting are impacting lives in Africa
MIT Sloan applied economics professor and IDSS affiliate Tavneet Suri researches the link between mobile banking apps and poverty levels in Kenya.
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New College of Computing reshapes MIT
IDSS is expected to join the new college, part of a $1 billion commitment to address the global opportunities and challenges presented by the prevalence of computing and the rise of artificial intelligence (AI).
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Suvrit Sra awarded NSF TRIPODS + X grant
Sra's cross-disciplinary research explores how machine learning can improve medical imaging.
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Philippe Rigollet awarded NSF BIGDATA grant
Research uses the theory of optimal transport to address data that are whole geometric objects rather than a collection of individual points, with applications in medical imaging, LiDAR for self-driving cars, and more.
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