MIT ReACT welcomes first Afghan cohort to its largest-yet certificate program
Empowering a global community of learners in displacement.
Empowering a global community of learners in displacement.
New effort empowers MIT researchers to shape real estate’s future and build responsibly and sustainably.
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
A new MIT-wide effort launched by the Institute for Data, Systems, and Society uses social science and computation to address systemic racism.
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.
A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.
A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.
Lincoln Laboratory leads a large-scale measurement campaign in New York City to improve air dispersion models and emergency protocols.
Measuring traffic properties requires vast amounts of data. Meshkat Botshekan, a PhD student working with the MIT CSHub, is discovering a more efficient and affordable physics-inspired alternative.
MIT biologists drilled down into how proteins recognize and bind to one another, informing drug treatments for cancer.
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
MIT scientists discuss the future of AI with applications across many sectors, as a tool that can be both beneficial and harmful.
In 2.C01, George Barbastathis demonstrates how mechanical engineers can use their knowledge of physical systems to keep algorithms in check and develop more accurate predictions.
David Gamarnik has developed a new tool, the overlap gap property, for understanding computational problems that appear intractable.