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BiRed Imaging, co-founded by Professor Satish Kandlikar, blends infrared camera capture, numerical simulation, and artificial intelligence-driven algorithms to accurately detect the presence, size, and location of tumors. The revolutionary process spares patients painful breast compression, radiation exposure, false alarms, and unnecessary anxiety.

Across the country, millions struggle to find timely or affordable mental health support. This imbalance was an inspiration for Ali Tosyali, who researched a potential assistive technology that could help practitioners identify potential disorders in a faster and efficient manner.

Backed by an award from the National Institutes of Health, Assistant Professor Stefan Schulze is using his expertise in the structure and function of proteins to work with a bacterial pathogen commonly associated with antibiotic resistance.

A new project funded by the National Institutes of Health is using artificial intelligence to map the full journey of illnesses and discover entirely new disease pathways.

RIT is celebrating a record year for sponsored research funding in fiscal year 2025, receiving $105 million.

An entry-level clinical doctorate in occupational therapy will launch in June 2026. The program, which will focus on innovative interventions and adaptive devices that extend patients’ functional skills, represents the university’s first clinical doctorate degree.

The interdisciplinary and collaborative Studio 930 program asks students to apply what they know, learn what they don’t, and design products that make life, or a single task, more efficient and accessible.

Aayush Kulkarni is participating in the International Visiting Research Student Program through RIT Global, which offers students from around the world the opportunity to collaborate with distinguished faculty-researchers from RIT.

Researchers at RIT developed new artificial intelligence techniques to extract and visualize information from standard-of-care biomedical data, providing a means for clinicians to better diagnose diseases and determine interventions.

Using a non-traditional, micro-organism separation method, researchers at RIT discovered a faster technique that can be used to distinguish cells that are resistant to antibiotics or cancer.

TechTarget speaks to Paloma Hamilton, fifth-year mechanical engineering student; Geoff Twardokus, electrical and computer engineering Ph.D. student; and Christopher Collison, director of RIT's AI Hub and Initiatives, about the innovative developments featured at Imagine RIT.

The process combines virology and mechanobiology, two distinct areas of study that had not been explored at the same time but might prove to be a way to better understand disease progressions to intervene earlier and improve patient outcomes.