Itani studying translation potential of secure & efficient software updates in industrial internet of things architectures
Grant and Award Announcement
Updates every hour. Last Updated: 15-Dec-2025 20:11 ET (16-Dec-2025 01:11 GMT/UTC)
Wassim Itani, Associate Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “I-Corps: Translation Potential of Secure and Efficient Software Updates in Industrial Internet of Things Architectures (IIoT).”
Much of the internet runs on systems written in the C programming language, but C has major security vulnerabilities. Now, computer science researchers have created a tool that safeguards these systems while developers migrate them into safer languages, a process that will take many years.
Melting glaciers may be silently setting the stage for more explosive and frequent volcanic eruptions in the future, according to research on six volcanoes in the Chilean Andes.
A Smithsonian-led team of researchers have discovered North America’s oldest known pterosaur, the winged reptiles that lived alongside dinosaurs and were the first vertebrates to evolve powered flight. In a paper published today, July 7, in Proceedings of the National Academy of Sciences, researchers led by paleontologist Ben Kligman, a Peter Buck Postdoctoral Fellow at the Smithsonian’s National Museum of Natural History, present the fossilized jawbone of the new species and describe the sea gull-sized pterosaur alongside hundreds of other fossils—including one of the world’s oldest turtle fossils—unearthed at a remote bonebed in Petrified Forest National Park in Arizona.
These fossils, which date back to the late Triassic period around 209 million years ago, preserve a snapshot of a dynamic ecosystem where older groups of animals, including giant amphibians and armored crocodile relatives, lived alongside evolutionary upstarts like frogs, turtles and pterosaurs.
Researchers have developed a technique that significantly improves the performance of large language models without increasing the computational power necessary to fine-tune the models. The researchers demonstrated that their technique improves the performance of these models over previous techniques in tasks including commonsense reasoning, arithmetic reasoning, instruction following, code generation, and visual recognition.