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Tech and law experts creating software that could solve a billion-dollar problem.

Johns Hopkins researchers found that algorithms trained on manufactured data can be even better than the real thing for important surgical tasks like X-ray image analysis or giving a robot the ability to detect instruments during procedures.

Computer scientist Daniel Khashabi discusses the pros and cons of the revolutionary natural-language processing tool—and predicts where it may head in the future.

In new commentary, researchers explain why developers must tailor AI systems and algorithms to their intended users.

Get to know Daniel Khashabi, who joins Johns Hopkins as an assistant professor of computer science and a member of the Center for Language and Speech Processing (CLSP).

Hopkins researchers present at the 17th International Symposium on Visual Computing (ISVC'22).

The research team has received funding from the Retina Society to automate the early detection of sickle cell retinopathy.

The new system identifies patients at risk for the illness, which is notoriously difficult to detect and develops quickly

The special issue on “Surgical Robotics and Computer-Integrated Interventional Medicine” provides an expert overview of the major application areas as well as the key enabling technologies in the growing field of surgical robotics.

A student-created app brings the biology lab experience to users' smartphones, paving the way for a more accessible lab education.

New work led by several universities, including Johns Hopkins, shows that neural networks built from biased Internet data teach robots to enact toxic stereotypes.

Scientists at Johns Hopkins University and Scripps Research have characterized 30 antibodies that recognize a wide range of coronaviruses - a step toward the next generation of coronavirus vaccines, which may help defend against a broader swath of viruses than current vaccines.