MIT Center for Real Estate launches the Asia Real Estate Initiative
New effort empowers MIT researchers to shape real estate’s future and build responsibly and sustainably.
Unlocking new doors to artificial intelligence
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
3 Questions: Fotini Christia on racial equity and data science
A new MIT-wide effort launched by the Institute for Data, Systems, and Society uses social science and computation to address systemic racism.
Injecting fairness into machine-learning models
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
Using artificial intelligence to find anomalies hiding in massive datasets
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.
Deep-learning technique predicts clinical treatment outcomes
A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.
Can machine-learning models overcome biased datasets?
A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.
Research aims to mitigate chemical and biological airborne threats
Lincoln Laboratory leads a large-scale measurement campaign in New York City to improve air dispersion models and emergency protocols.
3 Questions: What a single car can say about traffic
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.
Probing how proteins pair up inside cells
MIT biologists drilled down into how proteins recognize and bind to one another, informing drug treatments for cancer.
The downside of machine learning in health care
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
The promise and pitfalls of artificial intelligence explored at TEDxMIT event
MIT scientists discuss the future of AI with applications across many sectors, as a tool that can be both beneficial and harmful.
Physics and the machine-learning “black box”
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.
Tackling hard computational problems
David Gamarnik has developed a new tool, the overlap gap property, for understanding computational problems that appear intractable.
Understanding air pollution from space
Arlene Fiore uses satellite data paired with ground observations to refine our understanding of ozone smog and interactions with meteorology and climate.