معرفی
Matt LeBlanc is an Assistant Professor of Physics (Research) at Brown University, affiliated with the CMS Collaboration since 2024 and previously a core member of the ATLAS Collaboration from 2010–2023. His research focuses on experimental particle physics, particularly the analysis of hadronic objects and final states at the Large Hadron Collider (LHC). He employs advanced data science techniques, including machine learning and optimal transport algorithms, to study jet physics and search for new particles beyond the Standard Model. LeBlanc has contributed to jet reconstruction, calibration, and novel analysis methods in LHC data.
Education: Ph.D. in experimental particle physics from the University of Victoria (Canada). Postdoctoral appointments at the University of Arizona, CERN, and the University of Manchester (UK).
Research Interests: Jet substructure, hadronic object reconstruction, dark matter searches, QCD studies, radiation-hard detector development (e.g., MALTA sensors), and applications of AI/ML in physics. His work bridges experimental particle physics with computational science, addressing challenges in data processing for the High-Luminosity LHC era.
Key Contributions: Leader of physics analyses in the ATLAS Collaboration, coordinator for hadronic object reconstruction/calibration, developer of jet energy scale algorithms, and pioneer in applying optimal transport and topic modeling to particle physics data. His recent work emphasizes efficient data pipelines and simulations for future collider experiments.
