News

In December 2020, researchers led by Michael Birnbaum at the Feinstein Institutes for Medical Research demonstrated that an AI algorithm could predict psychiatric diagnoses up to 18 months before official diagnosis by analyzing Facebook messages and photos from 223 volunteers. The AI identified linguistic and visual markers associated with mood disorders and schizophrenia spectrum disorders, achieving accuracy comparable to traditional screening tools like the PHQ-9 survey. This approach suggests the potential for earlier detection and treatment of mental illnesses, though experts emphasize the importance of ethical considerations and privacy protections in such applications

In November 2020, Stony Brook University unveiled its Ookami supercomputer, powered by Fujitsu's A64FX Arm-based processor—the same technology behind Japan's Fugaku, the world's fastest supercomputer at the time. This installation marked a significant advancement in the university's computational capabilities, enabling researchers to tackle complex scientific challenges with enhanced efficiency. The Ookami project was supported by the National Science Foundation and aimed to provide the U.S. research community with access to cutting-edge high-performance computing resources

In November 2020, Stony Brook University's Institute for Advanced Computational Science installed the Ookami supercomputer, powered by Fujitsu's A64FX Arm-based processor—the same used in the world's fastest supercomputer, Fugaku. This HPE Apollo 80 system, supported by the National Science Foundation and managed with Bright Computing's Cluster Manager, offers researchers nationwide a platform to explore cutting-edge high-performance computing technologies.

In July 2020, researchers from Akai Kaeru LLC, affiliated with Stony Brook University, developed a machine learning tool to identify U.S. counties most at risk from the COVID-19 pandemic. By analyzing factors like population density, age distribution, and healthcare access, the tool aims to assist policymakers in targeting interventions and allocating resources effectively.