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Machine Learning applications at ATLAS

by Ke LI (IHEP)

122 Multidisciplinary Building

122 Multidisciplinary Building



The use of machine learning is increasing dramatically within ATLAS collaboration, in addition to the traditional applications in the context of improving the selections of interesting events against the overwhelming backgrounds, now ML is being widely applied in object reconstruction, identification. simulation and anomaly detection. Given the large and rapidly growing datasets,  ATLAS or other HEP experiment is one of the ideal places to develop and refine new ML algorithms. I will give an overview of the state-of-art ML applications at ATLAS including the tracking and vertexing, jet-tagging, fast simulation, unsupervised anomaly detection and preliminary study with the popular large language model.

About the Speaker:

Dr. Ke Li is an associated researcher at IHEP working on the AI application at BESIII. He earned the BS and Ph.D in particle physics from Shandong University and conducted postdoctoral research at the IHEP, SLAC and University of Washington, now he joined IHEP to develop and deploy the large language model for BESIII experiment. His primary focus is the application of state-of-art computing technologies and search for new physics and multi-quark states. He worked at the ATLAS and FASER experiment to search for heavy higgs and long lived particles at LHC, as well as offline software development including application of ML, the track and vertex reconstruction, and GPU-based software accelerator. He has led the vertex subgroup, Inner Detector Trigger group in ATLAS and track reconstruction and detector alignment working groups in FASER.



会议号 Meeting ID: 9176 8377 087
会议链接 Meeting URL:https://zoom.us/j/91768377087?pwd=T0ZOTDBmT3gwWUYxMVNQcXBsQnlXdz09
主持密码Host key:740212