### Data - 2016 Open Data NanoAOD ### Systematics - object-based: - JEC - weight-based: - e.g. b-tagging weight variations - modelling variations: - e.g. different $m_t$ ### Data-driven Background Estimation - Fake/ABCD estimation ### ML - S vs B for e.g. ttH measurement ### Sensitivity Optimization - Binning/ML Optimization ### Technical - coffea 2024 - workflow system (law) - XGBoost