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.
Reducing food waste to increase access to affordable foods
MIT alumni-founded Spoiler Alert matches major food brands with discount grocers to sell perishable products.
Meet the 2021-22 Accenture Fellows
The 2021-22 Accenture Fellows are bolstering research and igniting ideas to help transform global business.
Nonsense can make sense to machine-learning models
Deep-learning methods confidently recognize images that are nonsense, a potential problem for medical and autonomous-driving decisions.
Q&A: More-sustainable concrete with machine learning
MIT-IBM Watson AI Lab researchers aim to design concrete mixtures that use AI to shrink environmental footprint and cost, while recycling byproducts and increasing performance.