Researchers at the University of California, Davis have developed a hybrid system combining Fluorescence Lifetime Imaging (FLIM) and Interferometric Near-Infrared Spectroscopy (iNIRS) within a single optical probe for advanced, multimodal tissue analysis.

Researchers at the University of California, Davis have developed a non-adhesive, adjustable, and low-profile device designed to securely stabilize neonatal and pediatric endotracheal tubes while minimizing skin injury and pressure sores.

Researchers at the University of California, Davis have developed a hybrid quantum-classical computational workflow that enhances protein-protein binding site identification by quantum-assisted pruning of molecular structures prior to classical docking.

Researchers at Louisiana State University, New Orleans and the University of California, Davis have developed neuroprotective compounds that inhibit glutamine transport to reduce excitotoxic glutamate release, offering treatment for neurodegenerative diseases.

Researchers at the University of California, Davis have developed ethyl cellulose-based oleogels enhanced with fatty acid and acid salt complexes which offers a healthier and versatile alternative for structured lipids in food, cosmetic, and industrial applications.

Researchers at the University of California, Davis have developed a compact intraoperative sensing solution that helps clinicians identify cancerous tissue during minimally invasive procedures. The technology provides directional insight into the presence of approved molecular imaging tracers during surgery, addressing limitations of existing bulky or surface-limited tools. By offering intuitive, real-time guidance without disrupting surgical workflow, the approach supports more precise and confident tissue removal.

Researchers at the University of California, Davis have developed a compact system for directional detection of gamma rays and X‑rays without relying on heavy mechanical collimators. The approach improves the ability to localize radiation sources while reducing size, weight, and operational complexity compared to conventional solutions. The technology supports faster, more flexible use in clinical and industrial environments where directional radiation information is valuable.

Researchers at the University of California, Davis have developed a framework that enables autonomous systems to plan paths while accounting for how their actions influence surrounding actors. Unlike existing approaches that rely on reactive planning with fixed predictions or on computationally intensive multi-agent formulations, this technology uses a structured, data-driven interaction model within a tractable theoretical framework. The approach is designed for real-time deployment and supports analyzable performance and safety behavior under defined conditions. It enables more adaptive navigation in environments shared with people or other intelligent machines, improving operational efficiency, safety margins, and integration potential across a range of autonomous products.