Why some Wikipedia disputes go unresolved
Study identifies reasons for unsettled editing disagreements and offers predictive tools that could improve deliberation.
Machines that learn language more like kids do
Computer model could improve human-machine interaction, provide insight into how children learn language.
Model paves way for faster, more efficient translations of more languages
New system may open up the world’s roughly 7,000 spoken languages to computer-based translation.
HUBweek Policy Hackathon delivers local solutions
Citizens and data scientists produce actionable recommendations for high-priority Boston-area issues at Institute for Data, Systems, and Society student-run event.
Cryptographic protocol enables greater collaboration in drug discovery
Neural network that securely finds potential drugs could encourage large-scale pooling of sensitive data.
Automated system identifies dense tissue, a risk factor for breast cancer, in mammograms
Deep-learning model has been used successfully on patients, may lead to more consistent screening procedures.
Taming “information hazards” in synthetic biology research
Cryptography techniques to screen synthetic DNA could help prevent the creation of dangerous pathogens, argues Professor Kevin Esvelt.
MITx MicroMasters adds new pathways to master’s degrees
Learners from around the globe now have enhanced access to “blended” master’s programs at MIT and elsewhere.
3Q: David Simchi-Levi on advancing global retail operations through analytics and machine learning
David Simchi-Levi discusses insights from recent research in collaboration with some of the world's largest retailers.
New learning opportunities for displaced persons
Now accepting applications for new students, MIT ReACT Hub launched its first program in Jordan earlier this year with a certificate in computer and data science.
A game changer takes on cricket’s statistical problem
Laboratory for Information and Decision Systems alumnus and CSAIL lecturer Jehangir Amjad uses statistical methods to predict likely outcomes with limited data.
Reducing false positives in credit card fraud detection
Model extracts granular behavioral patterns from transaction data to more accurately flag suspicious activity.
Machine-learning system tackles speech and object recognition, all at once
Model learns to pick out objects within an image, using spoken descriptions.
Abdul Latif Jameel Clinic for Machine Learning in Health at MIT aims to revolutionize disease prevention, detection, and treatment
A key part of the MIT Quest for Intelligence, J-Clinic builds on MIT expertise across multiple scientific disciplines.
Model can more naturally detect depression in conversations
Neural network learns speech patterns that predict depression in clinical interviews.