Physics | Machine Learning | Computational Astrophysics
Master's graduate in Physics (Astronomy & Astrophysics) from the Institute of Space Technology with research experience in machine learning and statistical inference for physical science applications. Published work using Bayesian optimization and gradient boosting for prediction tasks.
Chinese Physics C (SCI-indexed, IF: 3.6)
DOI: 10.1088/1674-1137/ae19dc →Derived galaxy parameters using SDSS photometric data, Aladin Sky Atlas, Hubble-Lemaître Law, and Tully-Fisher relation.
Developed reproducible pipeline for Optuna-based hyperparameter search, CatBoost/XGBoost model training, and SHAP-based feature importance analysis.
Implemented and validated density-dependent point-coupling parametrization in relativistic mean-field code.
Institute of Space Technology, Islamabad, Pakistan
CGPA: 3.63/4.00 | Cum Laude
Thesis: AI-Driven Prediction of Nuclear Charge Radii: A Machine Learning Integration of Mean-Field Theory, Möller-Nix Model, and Experimental Data
University of Gujrat, Pakistan
GPA: 3.43/4.00
University of the Punjab, Lahore, Pakistan
72.2%
Institute of Space Technology (2025)
Second Position in B.Sc. Examination
Machine Learning & Cloud Computing
Aspire College Dina, Punjab
Courses: Computing Tools for Mathematics, C++ Programming, Machine Learning & AI fundamentals, Thermodynamics, Electronics
Aspire College Dina
Developed and deployed Moodle-based Learning Management System (LMS); coordinated academic programs and managed curriculum development initiatives.
I'm currently seeking doctoral opportunities in computational astrophysics, machine learning applications in physics, or related fields.