News

Johns Hopkins researchers have created a new kind of voice assistant to help older adults manage their health.

Johns Hopkins researchers have developed a new method that uses existing radiology reports to train AI models to locate tumors on CT scans more quickly and accurately.

Johns Hopkins computer scientists release new findings and a specialized dataset for training robots to recognize specific object parts.

A new study from Johns Hopkins finds that multilingual AI privileges dominant languages, deepening divides rather than democratizing access to information.

The Hopkins team’s new, open-source software dramatically improves scientists’ ability to detect genetic modifications that control gene activity.

New research ditches trial and error for faster, sharper, more trustworthy models.

Johns Hopkins computer scientists designed an interruption-handling system to facilitate more natural conversations with social robots.

Johns Hopkins computer scientists’ new training method, EigenLoRAx, promises to cut the environmental cost of fine-tuning large AI models.

New research provides first evidence of the use of browser fingerprints for online tracking.

QR code fraud is rising, so a Johns Hopkins team built a system to sniff out fakes.

Researchers from the Johns Hopkins University’s ARCADE Lab present the voice-controlled X-ray imaging system that earned a Best Paper Award at IPCAI 2025.

Johns Hopkins researchers show how different “odds” can teach AI models to admit when they’re not confident enough in an answer.