Mohamed Rayan Barhdadi

I am a third year student and researcher at Texas A&M University Qatar pursuing a bachelor in Electrical Engineering with minors in Mathematics and Physics. My research explores physics-informed geometric deep learning and neural 3D reconstruction, developing methods for sparse-view reconstruction using physical constraints. I'm passionate about creating work that makes a real difference in the scientific community and helps people—research that generates genuine insights rather than just better numbers.

My current project, PhysicsNeRF, integrates physics-based constraints into neural radiance fields for state-of-the-art 3D reconstruction from minimal input views, accepted at ICML 2025 Workshop in Vancouver. While my primary interests lie in geometric 3D physics-informed deep learning and AI for social good, I'm drawn to any machine learning research that creates meaningful impact. I follow research questions wherever they lead, as long as they advance scientific understanding and benefit society.

I am fortunate to work with exceptional advisors: Dr. Hasan Kurban (HBKU) and Dr. Hussein Alnuweiri (TAMU-Q) on neural rendering and 3D reconstruction, Dr. Hasan Kurban on high-impact AI for social good, and Dr. Halima Bensmail (QCRI) and Dr. Michael Aupetit (QCRI) jointly on flow-based clustering for high-dimensional data.