Ardavan Borzou

I am a physicist, data scientist, and founder of CompuFlair. My research focuses on developing physics-inspired machine learning methods by integrating ideas from physics, mathematics, and statistical inference.

I earned a PhD in Physics with research spanning both experimental and theoretical physics. As a member of the CMS Collaboration at the Large Hadron Collider, I worked on large-scale data analysis and statistical modeling, while my theoretical research explored an alternative formulation of gravity. My dissertation received my university's Best Dissertation Award and was later selected by Springer for publication in its Best Dissertation series.

Following appointments as a Data Science Fellow at the National Library of Medicine and as a postdoctoral researcher, I now develop novel machine learning methods for applications in biomedical research and other complex scientific domains.

Razie Yousefi

I am a computational biologist and data scientist with a background in physics, focused on applying quantitative modeling and machine learning to biomedical research.

My work combines bioinformatics, genomics, single-cell analysis, and machine learning to develop robust biomarker discovery frameworks with a focus on clinical translation.

Through CompuFlair, I am particularly interested in turning complex biological data into reproducible, clinically meaningful biomarker panels and predictive models.