I am a statistician and data scientist at the University of Wisconsin–Madison with a PhD and MPH, currently leading multiple interdisciplinary research projects at the intersection of medical imaging, machine learning, and population health. My primary research focuses on using CT-derived biomarkers to predict long-term health outcomes, particularly mortality and chronic disease burden, across large patient cohorts.

Alongside my research, I mentor undergraduate students in applied data science and model validation, integrating best practices in statistical reasoning and reproducible research. I serve on UW–Madison’s Machine Learning + X Leadership Committee. I’ve also developed workshops on AI in the classroom, applied improv for scientists, and strategic science communication.

At the heart of my work is a commitment to empathetic science communication — making complex tools accessible, engaging, and useful for both researchers and practitioners. With each project, I strive to blend technical excellence with a clear sense of purpose, impact, and collaboration.