Seeing the whole from some of the parts
A new technique in computer vision may enhance our three-dimensional understanding of two-dimensional images.
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Q&A: Chris Rackauckas on the equations at the heart of practically everything
Have a question about numerical differential equations? Odds are this CSAIL research affiliate has already addressed it.
Robots dress humans without the full picture
MIT researchers design a robot that has a trick or two up its sleeve.
Seeing an elusive magnetic effect through the lens of machine learning
An MIT team incorporates AI to facilitate the detection of an intriguing materials phenomenon that can lead to electronics without energy dissipation.
A new programming language for high-performance computers
With a tensor language prototype, “speed and correctness do not have to compete ... they can go together, hand-in-hand.”
The downside of machine learning in health care
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
Invisible machine-readable labels that identify and track objects
An MIT team develops 3D-printed tags to classify and store data on physical objects.
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.
Tackling hard computational problems
David Gamarnik has developed a new tool, the overlap gap property, for understanding computational problems that appear intractable.
Theoretical breakthrough could boost data storage
New work on linear-probing hash tables from MIT CSAIL could lead to more efficient data storage and retrieval in computers.
Using AI and old reports to understand new medical images
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
The boiling crisis — and how to avoid it
PhD student Madhumitha Ravichandran identifies the three main factors that trigger the boiling crisis through machine learning models.
Investigating materials for safe, secure nuclear power
A longstanding interest in radiation’s effects on metals has drawn Michael Short into new areas such as nuclear security and microreactors.
A streamlined approach to determining thermal properties of crystalline solids and alloys
MIT research team finds machine learning techniques offer big advantages over standard experimental and theoretical approaches.
Donated instrument provides undergraduate chemistry students high-level research experience
Cutting edge-tool reserved exclusively for students is fast, efficient, and environmentally friendly.