![An APL engineer modifies a robot to test its navigation algorithms](/sites/default/files/2023-01/IMG_Hero_Impact_AI_ML_Data.jpg)
Artificial Intelligence, Machine Learning, and Autonomy
Engineering with intelligence
Designing, building, and applying new technologies—especially those that include artificial intelligence—can be a double-edged sword: powerful and enabling on the one hand, but potentially biased and vulnerable to infiltration on the other.
From health care to planetary defense and national security, Johns Hopkins APL continues to make advances in AI to ensure the technology’s capabilities while identifying, minimizing, or eliminating its weaknesses.
A Laboratory-wide collaborative community of AI researchers and applied scientists works in domains from beneath the sea to outer space to innovatively incorporate autonomy, computer vision, machine learning, and other AI techniques across the breadth of our programs and projects. Internally funded AI exploration and research help us take bold steps in this realm to continue advancing AI for the good of the nation and the world.
Featured Facility
![Intelligent Systems Center](/sites/default/files/2023-10/IMG-ISC-Hero-Sept2023.jpg)
Intelligent Systems Center →
The Intelligent Systems Center (ISC) leverages APL’s broad expertise across national security, space exploration, and health to fundamentally advance the employment of intelligent systems for our nation’s critical challenges. The ISC acts as a focal point for research and development in artificial intelligence, robotics, and neuroscience at APL.
Related Projects
![Robotics researchers Craig Knuth and Adam Polevoy test machine learning algorithms for estimating traversable regions in complex environments. Such algorithms are necessary to enable robotic systems to autonomously traverse complex terrain.](/sites/default/files/2023-10/Project-Agile-Intelligent-Robots.jpg)
Agile and Intelligent Robots
![AlphaDogfight](/sites/default/files/2023-02/Project-Alphadogfight.jpg)
AlphaDogfight Trials
![ISC researchers Elizabeth Reilly and Jason Lee apply mathematical models to understand how different shocks impact food security.](/sites/default/files/2023-10/Project-AI-Climate.jpg)
Artificial Intelligence for Climate Action
![Climate Security](/sites/default/files/2023-01/IMG_Projects_Climate_Security_Cropped.jpg)
Climate Security
![Golden Horde](/sites/default/files/2023-02/Project-Golden-Horde.jpg)
Golden Horde
![Erik Johnson, a machine learning researcher at Johns Hopkins APL, demonstrating how agents are evaluated for lifelong learning on ISC-developed L2Explorer.](/sites/default/files/2023-10/Project-Lifelong-Learning-Machines.jpg)
Lifelong Learning Machines
![Optical physicist Michael Fitch models a prototype high-density diffuse optical imaging system, described in JJ Wathen et al. 2021.](/sites/default/files/2023-10/Project-Neural-Interfaces.jpg)
Neural Interfaces
![Raphael Norman-Tenazas, neuro-AI researcher, tests a robot navigation strategy inspired by the fruit fly connectome.](/sites/default/files/2023-10/Project-Neuroscience-Inspired-AI.jpg)
Neuroscience-Inspired Artificial Intelligence
![Neil Fendley, machine learning researcher, demonstrates a backdoor adversarial attack he embedded in a computer vision application.](/sites/default/files/2023-10/Project-Robust-Resilient-AI.jpg)
Robust and Resilient Artificial Intelligence
![Swarming unmanned surface vehicles](/sites/default/files/2022-12/IMG_Projects_Swarming-Surface-Vehicles.jpg)
Swarming Uncrewed Surface Vehicles
![Autonomous swarming unmanned surface vessels (SUSVs) — equipped with Johns Hopkins APL-developed hardware and autonomy software](/sites/default/files/2022-12/IMG_Projects_Unmanned_Surface_Vessel_Perception.jpg)
Uncrewed Surface Vessel Perception
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