I’m a Master’s student in Applied & Engineering Physics at the Technical University of Munich, holding a Bachelor’s in Physics Engineering from Istanbul Technical University. My academic background merges theoretical physics with hands-on experience in data analysis and machine learning. 

I focus on the intersection of computational methods and physical sciences. My bachelor thesis  spans deep learning applications in High Energy Physics — particularly dark matter detection with the CMS experiment at CERN — and statistical methods in plasma physics, astrophysics, and semiconductor materials. 

My coursework reflects this interdisciplinary path and includes: Plasma Physics, Gravitational Lensing, Statistical Learning in Physics, Machine Learning for Physicists, Optoelectronics, and Advanced Statistical Physics. I have also worked on LSTM-based space weather forecasting with NASA data, EPR simulations in ZnO, and light diffraction in organic materials. 

Equipped with a solid foundation in Python, C++, SQL, and scientific computing, I strive to develop data-driven frameworks to reveal underlying patterns in complex physical systems—ranging from subatomic interactions to large-scale cosmic phenomena.