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Artificial Intelligence Technology

Our group develops fundamental and enabling artificial intelligence (AI) technologies to solve complex challenges and to advance AI for the nation. In close collaboration with groups across the Laboratory, as well as with MIT and the greater academic community, our team is working at the frontier of research in AI for national security. Current research areas include applying AI to fuel scientific discovery of materials and biomaterials; exploring network science and its applications; employing AI as a teammate in making decisions; developing technology to increase trust in AI; and investigating the broad area of responsible AI and ethics. The group also develops courses and holds workshops to educate the workforce of the future and accelerate the adoption of AI in key national security domains.

Our research team includes many of the Laboratory’s top AI experts with knowledge in deep learning architectures, adversarial learning, probabilistic programming, reinforcement learning, network science, human–computer interaction, multi-modal data fusion, and autonomous systems. Our computing capabilities provide ample opportunity to do research at scale on both closed and publicly available datasets. We provide a vibrant and collaborative research environment with close ties to academia and sponsors with critical mission needs.

Featured Projects

A schematic showing the explainable artificial intelligence concept.
We are developing tools to enhance the explainability of artificial intelligence (AI) systems for improved human-AI collaboration.
ASERT square icon
We are developing scalable tools and techniques to accelerate the design and evaluation of reliable, mission-ready artificial intelligence systems.
A team of autonomous aerial vehicles learns to collaborate on a complex task by hypothesizing the team’s performance if an individual vehicle takes a risky action that leads to its destruction.
Teams of autonomous systems learn collaboration strategies by hypothesizing how the team would perform if one system followed alternative trajectories or was eliminated from the team.
Lincoln Laboratory AI Education and Training
This initiative will deliver tailored educational content to trainees to expand their basic understanding of artificial intelligence (AI) and the applications to national security missions.

Advancing Our Research


Probabilistic coordination of heterogeneous teams from capability temporal logic specifications

Apr 1
IEEE Robot. Autom. Lett., Vol. 7, No. 2, April 2022, pp. 1190-7.

Fast decomposition of temporal logic specifications for heterogeneous teams

Apr 1
IEEE Robot. Autom. Lett., Vol. 7, No. 2, April 2022, pp. 2297-2304.

Our Staff

View the biographies of members of the Artificial Intelligence Technology group.