Serious game experimentation is used to analyze human decision making.

Homeland Sensors and Analytics

Machine learning is changing the paradigm of many jobs. Our group develops and adapts machine learning technology to help police officers prevent crime, transportation workers plan efficient routes, heath care officials improve diagnoses, and military leaders plan effective missions. Our technologies are used to analyze many different types of data, including video and images, text, transactions, metadata, and combinations of these data. We customize the technology to the problem at hand and often include operator feedback to control the algorithms. To help us design and evaluate our machine learning solutions, we use systems analysis methods, including serious game experimentation, that considers the operators and their environment as part of the system. We also develop operator-adaptable software platforms to deploy our algorithms as prototype systems and to accelerate human collaboration. The technical solutions we develop help create a world in which humans and machines work as partners.

Featured Projects

Researchers test the prototype standoff microwave imaging system. The antennas emit radio signals that reflect off the person standing in front of the array; the system processes the reflections to create the image on the monitors in the background.
The system can rapidly and discreetly detect threat items concealed under clothes or hidden in bags of people in crowded public spaces.
The FOVEA tool is just one of Lincoln Laboratory's efforts to help the Department of Homeland Security Science and Technology Directorate protect public spaces such as subways from attacks.
The tool lets security officials quickly analyze video surveillance footage and track incidents of interest.

Advancing Our Research


29 - 30
Endicott House, Dedham, MA