Youssef Abdulghani

Physics PhD Candidate

Welcome

Youssef Abdulghani

My intrinsic thirst for knowledge has led me on a journey of discovery in the fascinating fields of astrophysics and AI. This journey has endowed me with a profound understanding of the universe's most enigmatic phenomena, ranging from the intricate dance of X-ray black hole binary systems to distance metric learning in embedding manifolds. I eagerly anticipate the next chapter of this journey, where I will continue to leverage my skills for new discoveries through research or by contributing to the betterment of the world through industry!

My Research

Data-driven science at the intersection of astrophysics, statistics, and machine learning

Through support by NASA’s Swift Guest Investigator program, I conducted research on estimating the distance to black hole X-ray binaries using a Bayesian approach. My work involved developing a statistical framework that leverages the best current observational and theoretical knowledge to produce distance probability densities and make it readily available to the astrophysical community. My current research on one hand focuses on utilizing these distances to investigate the population of black hole X-ray binaries in our galaxy. On another hand, I'm working on accretion disk inclination angle inference using machine learning. Utilizing both spectral and temporal data.

Projects

BH-LMXBs distance: probability calculator, quick estimation tool, known sources estimates

X-ray Hardness-Intensity Monitoring: Swift J1727.8-1613, GX 339-4

Check out all my projects on GitHub

Publications

Contact

Email me.

Connect with me on LinkedIn.

You can download my CV here.