Medical Device Design
End-to-end development for the clinic: concept, CAD, electronics, prototyping, and bench validation, designed around real perioperative workflows.
Biomedical engineer designing medical devices and monitoring systems for the operating room, from renal oxygenation monitoring to acute kidney injury detection.
Ali Ramezani is a Ph.D. candidate in Biomedical Engineering at the University of Utah, where he designs medical devices and monitoring systems for the operating room. His doctoral research centers on renal oxygenation monitoring: recovering trustworthy kidney-oxygen signals from urinary oxygen tension measured at the bedside, so clinicians can detect acute kidney injury (AKI) risk earlier.
His work spans the full arc of translational engineering, from identifying an unmet clinical need and modeling the underlying physics to building and validating sensing hardware and algorithms, then carrying them toward the operating room and intensive care unit. Recent projects include Nephrova, an intraoperative kidney-oxygenation monitoring system, and Medistant, a multimodal assistant for identifying and guiding medical devices in the OR.
A 2026 MIT Catalyst Fellow, he works at the intersection of engineering, anesthesiology, and critical care, collaborating with clinicians to move ideas from prototype to patient. He is an inventor on multiple U.S. and international patent applications. Before his doctoral studies, he completed a top-ranked M.S. in Biomedical Engineering and built a decade of design and entrepreneurial experience across medical and industrial engineering.
The work runs from sensing hardware and instrumentation to the algorithms and interfaces that make a measurement useful in the operating room. Kidney oxygenation is one applied thread within a broader medical-device program.
End-to-end development for the clinic: concept, CAD, electronics, prototyping, and bench validation, designed around real perioperative workflows.
Bedside and intraoperative monitors that turn raw physiological signals into information clinicians can act on in real time.
Tools built for the realities of the OR, from continuous organ monitoring during surgery to fast, trustworthy device identification and guidance.
Optical and electronic sensors, calibration methods, and the signal chain that makes a bedside measurement accurate and trustworthy.
Algorithms that separate physiological signal from artifact: transit-time tracking, diffusion correction, and sample-validity models.
One applied thread: monitoring kidney oxygenation from urinary oxygen tension to flag acute kidney injury risk earlier than today's markers.
An intraoperative monitoring system that makes the kidney visible in real time. Nephrova continuously measures urinary oxygen and flow as a surrogate for renal hypoxia risk, with a sensing module that connects inline between the urinary catheter and the collection bag, fitting standard OR workflow without disrupting care.
A multimodal assistant that turns a photo, QR scan, or NFC tap into the correct device page in seconds, surfacing manuals, checklists, and a device-scoped AI assistant for perioperative teams.
An algorithm that tracks how long urine takes to traverse the catheter, establishing sample validity so a bedside oxygen reading reflects the kidney rather than the tubing.