Graduate Student Researcher
CurrentDeveloped high-fidelity Monte Carlo-based particle detector models using generative architectures like VAEs, GANs, and NFs, enhancing detection accuracy in the ATLAS experiment. Engineered and integrated software components for the ATLAS tagger system, improving data analysis workflows, and applied machine learning techniques in C++ and Python to collaborate with international teams. My work involved handling large-scale datasets, conducting end-to-end analysis, and contributing to research publications by simulating particle detector responses using generative models.