Science can be difficult to explain to the public. Explaining a theoretical science concept to high school students requires a new way of thinking altogether, which is precisely what researchers at UC San Diego did when they orchestrated a dance with high school students at Orange Glen High School in Escondido as a way to explain topological insulators. The experiment was led by former graduate student Matthew Du and UC San Diego Associate Professor of Chemistry and Biochemistry Joel Yuen-Zhou.

The unique properties of baseball’s famed “magic” mud, which MLB equipment managers applied to every ball in the World Series, have never been scientifically quantified — until now. In a new paper in Proceedings of the National Academy of Sciences (PNAS), researchers at the University of Pennsylvania School of Engineering and Applied Science (Penn Engineering) and School of Arts & Sciences (SAS) reveal what makes the magic mud so special.

Covered recently in the prestigious journal Nature Medicine, BiomedGPT is a new a new type of artificial intelligence (AI) designed to support a wide range of medical and scientific tasks. This new study, conducted in collaboration with multiple institutions, is described in the article as "the first open-source and lightweight vision–language foundation model, designed as a generalist capable of performing various biomedical tasks."

"This work combines two types of AI into a decision support tool for medical providers," explains Lichao Sun, an assistant professor of computer science and engineering at Lehigh University and a lead author of the study. "One side of the system is trained to understand biomedical images, and one is trained to understand and assess biomedical text. The combination of these allows the model to tackle a wide range of biomedical challenges, using insight gleaned from databases of biomedical imagery and from the analysis and synthesis of scientific and medical research reports."