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 physicist, computational biologist, and data scientist specializing in biomedical data analysis and machine learning. My research focuses on developing computational methods for analyzing complex biological datasets, with particular interests in genomics, single-cell transcriptomics, neuroscience, and precision medicine.

My background in physics has provided a strong foundation in mathematical modeling and quantitative analysis, which I apply to biological and biomedical research. I have worked on a wide range of data-intensive projects, integrating statistical methods, machine learning, and computational biology to uncover insights from high-dimensional datasets.

Through CompuFlair, I develop computational tools and data analysis pipelines while collaborating with researchers to translate complex biological data into meaningful scientific discoveries.