معرفی
Ho Fung Tsoi is a Postdoctoral Researcher in the Department of Physics and Astronomy at the University of Pennsylvania, affiliated with the School of Arts & Sciences. His research focuses on experimental particle physics at the CERN Large Hadron Collider (LHC), particularly leveraging machine learning techniques to analyze collision data. He contributes to the CMS experiment, focusing on topics such as Higgs boson physics, dark matter searches, heavy flavor dynamics, and detector performance optimization. His work includes both theoretical method development (e.g., symbolic regression algorithms) and experimental analyses of rare particle decays, jet quenching effects in heavy-ion collisions, and supersymmetry model testing.
Key research directions include studying scalar boson interactions, top quark dynamics, and precision measurements of strong interaction parameters. He has published extensively on topics ranging from LHC detector calibration to searches for exotic particles and new physics beyond the Standard Model. His machine learning projects aim to improve background estimation and enhance signal extraction in high-energy physics datasets.
Notable contributions include the SymbolFit algorithm for parametric modeling and the ABCDisCoTEC method for variable-independent background estimation. His work often bridges computational innovation with experimental particle physics, addressing challenges in both data analysis and theoretical interpretation.
- Primary affiliation: University of Pennsylvania School of Arts & Sciences
- Experimental collaborations: CMS Collaboration at CERN
- Key facilities: Large Hadron Collider (LHC), CMS detector
