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.
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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.
Researchers construct molecular nanofibers that are stronger than steel
Self-assembly of Kevlar-inspired molecules leads to structures with robust properties, offering new materials for solid-state applications.
“Futurizing” undergraduate teaching
Associate Professor Michael Short’s innovative approach can be seen in the two nuclear science and engineering courses he’s transformed.
A cool advance in thermoelectric conversion
A quantum effect in topological semimetals demonstrated by MIT researchers could allow for the utilization of an untapped energy source.
Algorithm quickly simulates a roll of loaded dice
Approach for generating numbers at random may help analyses of complex systems, from Earth’s climate to financial markets.
