I’m a Physics major deeply drawn to the intersection of mathematics, computation, and real-world problem-solving. My passion lies at the crossroads of Computational Sciences—where physical theories meet computational models—and Artificial Intelligence & Machine Learning, particularly in building systems that learn from data and reason about complex phenomena.
I’m driven by the challenge of applying computational and AI-driven approaches to tackle real-world problems, from simulating natural systems to developing intelligent models that complement first-principles understanding. My goal is to bridge theoretical insight with practical implementation—turning equations into code, and ideas into impact.
Whether it's through physics-informed machine learning, scientific computing, or statistical modeling, I aim to contribute to solutions that are both grounded in theory and scalable in practice. I believe the future belongs to those who can think critically, compute efficiently, and learn continuously.
💡 Interested in collaborating on projects in computational science, AI/ML, or simulation-driven problem-solving.
📫 Explore my repositories or reach out—I'm always learning, always building.