A UVA Engineering researcher is using AI to develop computational tools that improve infectious disease forecasting, guide public health decisions and strengthen disease surveillance.

A UF-led study of nearly 100,000 young adults found an association between using generative AI for health-related questions and screening positive for clinically significant anxiety and depression. Young adults who used AI tools like ChatGPT and Claude for health questions had 52% greater odds of screening positive for anxiety and 46% greater odds for depression. The findings do not show that AI use causes anxiety or depression but point to the need for more research into how young people use AI to understand health symptoms and concerns.

The U.S. National Science Foundation (NSF) awarded DRI’s Alison Murray, molecular microbial ecologist and biological oceanographer, $18.4 million to lead a project that will pave the way for the next generation of Antarctic research. Titled “Genome Infrastructure catalyzing next Generation Antarctic Data, Access, Tools, and Analytics” (GIGA DATA), the work will produce an extensive database of genetic information. More than 250 Antarctic species’ genomes will be sequenced (including algae and mosses, terrestrial and marine invertebrates, birds, fish and marine mammals) alongside 600 ecosystem samples representing tens of thousands of microbial and viral genomic datasets. This project will unite these new data together with existing Antarctic sequencing efforts under a new, artificial intelligence-enabled cyberinfrastructure. The resulting digital platform will serve as an open, accessible data science gateway to Antarctic life. 

With the advancement of deep-space missions such as crewed lunar exploration and Mars exploration, artificial intelligence (AI) technologies are being increasingly embedded into aerospace engineering management processes, and managers' AI competency has become a critical factor affecting mission delivery performance and safety compliance. However, traditional project management competency models have been primarily constructed around process control and redundancy design within deterministic systems, failing to explicitly address governance challenges introduced by AI integration—including black-box opacity, accountability allocation, traceable review of AI outputs, and accountability mechanisms for assisted decision-making. Although existing NASA and ESA frameworks provide fundamental support for aerospace project delivery, AI-related competencies in aerospace management exhibit inherent interdependencies. Managers are required to continuously balance delivery schedules and cost pressures against mission assurance obligations such as verification and validation, configuration control, and compliance, making it impossible to simply represent AI competency as a linear list of attributes. Therefore, how to construct an AI competency assessment framework that captures governance priorities and multi-attribute interdependencies has become a critical issue urgently to be addressed in aerospace engineering management in the AI era.

SAN ANTONIO — September 29, 2026 —Southwest Research Institute (SwRI) and Australia-based Adelaide University are exploring quantum radio frequency (RF) sensing, sensemaking, which is quantum signal interpretation and analytics, and related technologies through a new three-year memorandum of understanding (MOU) signed by both organizations. A joint research team launched first-phase, hands-on evaluations of superconducting quantum RF sensors for signals intelligence applications at the Jesper Munch Quantum Laboratories at Adelaide University in South Australia. Signals intelligence is the field of collecting, intercepting and analyzing electronic signals to support defense, communications and emergency response.

Precision nutrient management in high-density orchards is critical for yield and fruit quality, yet accurately gauging the nitrogen status of individual trees remains a challenge.