​Stony Brook University has received Graduate Assistance in Areas of National Need (GAANN) fellowships for six departments: psychology, civil engineering, computer science, biomedical engineering, materials science and chemical engineering, and electrical and computer engineering. Each department offers five fellowships annually, totaling 30 graduate student fellowships per year across the university.

​A study published on Hospimedica highlights the effectiveness of artificial intelligence (AI) in detecting fractures on X-rays. The research demonstrated that AI assistance reduced missed fractures by 29% and increased diagnostic sensitivity by 16% for single fractures, and by 30% for cases involving multiple fractures. Additionally, AI improved specificity by 5% and shortened X-ray reading ti

​Stony Brook University's Computer Science faculty developed an in-house COVID Surveillance Screening platform, deployed by the Renaissance School of Medicine. This system enhances the university's ability to monitor and manage COVID-19 cases effectively. By leveraging advanced computational techniques, the platform supports timely identification of potential outbreaks, contributing to the heal

​Researchers from the University of Waterloo, in collaboration with DarwinAI and radiologists from Stony Brook School of Medicine and Montefiore Medical Center, have developed an AI tool to assess the severity of COVID-19 lung infections using chest x-rays. This deep-learning AI analyzes the extent and opacity of infections, aligning closely with expert radiologist evaluations. The technology a

​Researchers from the University of Waterloo, in collaboration with DarwinAI and radiologists from Stony Brook School of Medicine and Montefiore Medical Center, have developed an AI tool to assess the severity of COVID-19 lung infections using chest x-rays. This deep-learning AI analyzes the extent and opacity of infections, aligning closely with expert radiologist evaluations. The technology a

A recent study highlights the transformative impact of machine learning on weather forecasting. By leveraging advanced algorithms, researchers have developed models that significantly enhance the accuracy and efficiency of weather predictions. These machine learning techniques outperform traditional numerical methods, offering faster forecasts with reduced computational demands.

Stony Brook University and Brookhaven National Laboratory have jointly awarded $317,000 in seed funding to eight collaborative research teams. This initiative aims to foster interdisciplinary projects that leverage the strengths of both institutions, promoting innovation in various scientific fields. The selected teams will utilize the funds to advance their research endeavors, contributing to