Conducted research at the intersection of machine learning and high energy physics, developing novel computational methods for analyzing particle physics data.

Responsibilities

• Developed machine learning algorithms for unfolding and deconvolution in particle physics experiments
• Collaborated with international teams on ATLAS experiment data analysis
• Published research in peer-reviewed journals and presented at international conferences
• Mentored undergraduate researchers on machine learning projects

Technologies & Skills

• Python, TensorFlow, PyTorch, JAX
• Statistical inference and Bayesian methods
• High-performance computing on NERSC systems
• Particle physics simulation and analysis frameworks