Team
PIMAP is a collaborative research effort. Confirmed team information will appear here as it is prepared.
ML Researcher
Machine learning research
David contributes to PIMAP's machine learning research, working on the modeling and evaluation questions behind pressure injury prediction. He helps design and run the experiments that test whether prepared features carry a usable signal.
ML Researcher
Machine learning research
Jonathan contributes to PIMAP's machine learning research, focusing on model experimentation and the preparation of features used to study pressure injury risk. He works on making those experiments reproducible and their results easier to interpret.
Advisor
Networked monitoring systems and research direction
Katia is a professor of computer science and engineering at UC Santa Cruz and director of the Inter-Networking Research Group, whose work includes monitoring systems applied to patient care. She advises PIMAP on research direction.
University of California, Santa Cruz
Advisor
Engineering and product direction
Hitesh advises PIMAP on engineering and product direction, helping translate research into usable, well-built software. He brings a practical focus on turning early prototypes into maintainable, dependable systems.
Advisor
Machine learning and evaluation methods
Collin advises PIMAP on machine learning methods and evaluation, bringing a research perspective on applying models to clinical questions.