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A simple illustration of a DNA strand
In the Media

Creating ‘DNA barcodes,’ researchers work to speed up forensic analysis

February 14, 2019
R&D Magazine
a dried-out lagoon

Workshop explores national security repercussions of climate change

February 11, 2019
A researcher holds a tablet showing the MNOISE app while a user wears the MNOSIE earpiece.

New noise monitor helps protect warfighters from hearing loss

January 29, 2019
Brian Telfer was presented with the IEEE Region 1 Technological Innovation Award for his significant contributions to technologies that protect national security. Photo: Glen Cooper
Awards

Brian Telfer receives IEEE Technological Innovation Award

January 28, 2019
an abstract-looking image of neurons in the brain. Red "strings" across the image are neurons that express a certain protein.
In the Media

Mapping the brain, cell by cell

December 17, 2018
MIT News
A photo of a large truck picking up debris lining a street

Lidar scans over the Carolinas accelerate hurricane recovery

December 13, 2018
The principal researchers of MIT Lincoln Laboratory's 12 finalists for 2018 R&D 100 Awards are pictured here with Lincoln Laboratory Director Eric Evans (far left). The principal researchers of the 10 winning technologies hold up their award plaques.
Awards

Ten MIT Lincoln Laboratory innovations win R&D 100 Awards

November 21, 2018
A U.S. Coast Guard responder offshore is able to access real-time information from NICS' onshore computers on a mobile device. Photo: Amna Greaves
Awards

Lincoln Laboratory honored for providing access to technology for disaster response

September 10, 2018
TbD-net solves the visual reasoning problem by breaking it down to a chain of subtasks. The answer to each subtask is shown in heat maps highlighting the objects of interest. This process allows analysts to see the network's “thought process.”

A new artificial intelligence system solves problems through human-like reasoning

September 4, 2018
From left to right are Melva James, Stephanie Carnell, Jonathan Su, and Neela Kaushik, the team developing Adaptable Interpretable Machine Learning (AIM) at Lincoln Laboratory. Photo: Glen Cooper

Replacing black box machine learning with interpretable models

September 4, 2018
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