Today, High Energy Physics (HEP) research is at a crossroads. While the Large Hadron Collider (LHC) keeps accumulating data to establish the Standard Model on a solid footing, compelling theoretical underpinnings point to the existence of new physics at higher energy scales. In the future, the High Luminosity LHC will precisely measure the properties of the Higgs boson, using a few thousand petabytes of data. Many other precision experiments in HEP are under construction or going to start soon. Hence, the future course of the field will be largely data-driven.Machine Learning techniques will be heavily employed in analyzing this humongous data for possible hints of new physics. Already, remarkable progress has been achieved in developing different classification, identification, characterization, and estimation strategies for use in the searches performed at LHC.The primary purpose of this meeting is human resources development and capacity building in frameworks related to deep machin...
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