Back to landing

Machine Learning for LHCb

As part of Physics Coursework at Imperial College London, I led the machine learning team analysing decay product distributions from the Large Hadron Collider beauty (LHCb) experiment. We benchmarked TensorFlow and XGBoost pipelines for signal classification, used in downstream analysis. Distinction, highest score in cohort.

  • Tools: TensorFlow, XGBoost, NumPy, Matplotlib

View slides