News

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.

Johns Hopkins computer scientists tackle a sometimes dangerous language model flaw that misunderstands words like “don’t” and “no.”

Genome annotation is falling behind how fast genomes can be assembled—but Johns Hopkins researchers have created a tool that can change that.

In their quest to develop a co-creative AI partner, Johns Hopkins computer scientists discover valuable insights about the limitations and ethical considerations of current generative AI models.

Johns Hopkins researchers are using artificial intelligence to reduce delays in cancer treatment and ensure patient safety.