I combine physics, mathematics, scientific computing, and artificial intelligence to investigate complex systems, analyze scientific data, and develop computational tools for modern research challenges. My goal is to contribute to theoretical and computational physics research while leveraging machine learning for scientific discovery.
I am a Physics graduate with strong interests in theoretical physics, computational modeling, scientific machine learning, and numerical simulation. My background in mathematics and physical sciences, combined with programming and machine learning skills, allows me to approach scientific problems from both analytical and computational perspectives. I am actively seeking research collaborations, graduate study opportunities, and projects at the intersection of physics, mathematics, and AI.
Numerical simulation of gravitational interactions between multiple celestial bodies using computational physics techniques.
Python-based toolkit for analyzing and visualizing experimental and simulation datasets.
Application of machine learning techniques to extract patterns and insights from scientific datasets.
Implementation of numerical methods for solving physical systems described by differential equations.
Email: saide76556@gmail.com
GitHub: github.com/physicsaiml
LinkedIn: linkedin.com/in/physicsaiml
"Physics provides the language of nature. Mathematics provides the framework. Artificial Intelligence provides the tools to explore both at scale."