Artificial Intelligence (AI) is rapidly advancing—and with it, the promise of solving some of academia’s toughest problems. But while many researchers focus on using AI to find answers, Associate Professor Hiroshi Kera of the Institute for Advanced Academic Research/Graduate School of Informatics is asking a different question: How can we design better problems for AI to solve?

A specialist in algebra—the branch of mathematics that explores equations using symbols and letters, from the quadratic equations taught in junior high and high school to far more abstract structures—Dr. Kera is working at the intersection of computational algebra and AI. By combining computer-based algebraic computation with AI, he aims to open new frontiers in mathematical discovery. We spoke with Dr. Kera about how AI could reshape—and expand—the world of mathematics.

UVA’s Yu Meng wins NSF CAREER Award to help AI learn from messy, incomplete data — for better results in everything from accurate hospital records to scientific discovery.

The All-Hazards Preparedness Game is a virtual reality-based training platform that helps individuals develop disaster preparedness and decision-making skills through immersive simulations of emergencies such as evacuations and shelter-in-place scenarios. Initially designed and tested with older adults, the technology provides a safe, controlled environment for practicing protective actions without the risks and ethical challenges associated with studying real-world disasters. Built using platforms such as Unity and Blender, the game enhances engagement, learning, and preparedness through realistic interactive experiences. Potential applications include community preparedness programs, emergency management training, education, and resilience planning. The patent-pending technology is at TRL 5 and available for licensing.

Artificial intelligence (AI) scribes can reduce the time physicians spend documenting patient visits by 69.1% during simulated primary care appointments, according to research led by University of Toronto PhD student LaShawn Murray. 

The study — published in the journal JAMIA Open, and co-authored with University of Toronto professor Enid Montague and Dr. Onil Bhattacharyya of Women’s College Hospital — involved nine physicians completing simulated patient encounters both with and without the use of AI scribes. These digital tools are capable of recording audio and using it to generate structured, regulatory-compliant clinical notes for a patient’s medical chart — the record physicians use to document their care. 

The researchers used video recordings of each appointment to analyze how physicians spent their time. They found that when the scribes were in use, the doctors spent significantly less time documenting.