In The News

MIT community in 2023: A year in review
MIT community in 2023: A year in review

Top Institute stories dealt with a presidential inauguration, international accolades for faculty and students, “Dialogues Across Difference,” new and refreshed community spaces, and more.

MIT’s top research stories of 2023
MIT’s top research stories of 2023

A cheaper water desalination device, a wearable ultrasound scanner, and the discovery of an Earth-like exoplanet were some of MIT News’ most popular articles.

Professor Emeritus Frederick Hennie, expert in computation and leader within MIT EECS, dies at 90
Professor Emeritus Frederick Hennie, expert in computation and leader within MIT EECS, dies at 90

The highly influential professor served for 25 years as executive officer of the Department of Electrical Engineering and Computer Science.

Using AI, MIT researchers identify a new class of antibiotic candidates
Using AI, MIT researchers identify a new class of antibiotic candidates

These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.

Navy officer deepens her engineering and leadership skills at MIT
Navy officer deepens her engineering and leadership skills at MIT

Through the GradEL program, Lieutenant Asia Allison is developing a deeper understanding of her own background and profile as a leader.

Nanoparticle-delivered RNA reduces neuroinflammation in lab tests
Nanoparticle-delivered RNA reduces neuroinflammation in lab tests

MIT researchers find that in mice and human cell cultures, lipid nanoparticles can deliver a potential therapy for inflammation in the brain, a prominent symptom in Alzheimer’s.

Image recognition accuracy: An unseen challenge confounding today’s AI
Image recognition accuracy: An unseen challenge confounding today’s AI

“Minimum viewing time” benchmark gauges image recognition complexity for AI systems by measuring the time needed for accurate human identification.

Computational model captures the elusive transition states of chemical reactions
Computational model captures the elusive transition states of chemical reactions

Using generative AI, MIT chemists created a model that can predict the structures formed when a chemical reaction reaches its point of no return.

2.009 gets “Wild!”
2.009 gets “Wild!”

Six teams of mechanical engineering students pitched “wild” products during the annual capstone course prototype launch event.

Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows
Three MIT students selected as inaugural MIT-Pillar AI Collective Fellows

The graduate students will aim to commercialize innovations in AI, machine learning, and data science.

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