Eleni Stamatelou is a machine learning researcher and educator whose work is driven by a clear goal: using data science to improve healthcare and save human lives. Her expertise includes signal processing, deep learning, and data-driven design, a combination well suited to medicine, where the raw material is often noisy physiological signals and the cost of a wrong prediction is measured in patient outcomes.

Eleni works on the practical challenges of turning models into deployed clinical tools, including sepsis prediction and machine learning for low-resource clinical environments. That means designing robust models for imperfect clinical data, validating them with the care patient safety demands, and thinking hard about how ML integrates into clinical workflows where infrastructure is limited. It is work that sits squarely between research and practice.

As an educator as well as a researcher, Eleni shares what she has learned about building healthcare machine learning systems, helping the next generation of data scientists approach medical applications with both ambition and humility.