News

Researchers use advanced models to uncover critical thresholds in global ocean circulation, highlighting potential climate impacts.

New model predicts how much time proposed rail line could save commuters.

Engineering student’s model could give faster turns the green light.

New approach could help powerful AI models create realistic content using less energy.

Johns Hopkins team develops a dimension-agnostic method for machine learning.

Johns Hopkins team develops a way to personalize antiretroviral therapy to reduce side effects.

3D printed objects help students visualize complex concepts.

Luana Ruiz, a mathematician at Johns Hopkins, leads team in efficient and cost-effective approach for graph neural networks, unveiling a novel method to teach computers with small data samples.

Approach promises to improve accuracy of celestial object matching.

Innovative new method could make computer calculations more efficient.

Quanta Magazine features Ben Grimmer's recent study on a traditional assumption in gradient descent, revealing that breaking the rule of small steps can lead to nearly three times faster results on optimization problems.

Alumna and data scientist at the Johns Hopkins University Applied Physics Laboratory uses statistical hypothesis testing to determine whether a performance discrepancy in AI can be either the product of bias or random chance.