In this talk some recent developments in the context of jet physics and their structure are reviewed. In particular, new substructure variables that aim to probe colour flow in particle events are introduced. These variables find a natural application in the context of tagging a boosted Higgs boson. In the second part of the talk, the use of machine-learning algorithms in the context of jet physics is reviewed and the first attempts to achieve a systematic first-principle understanding of their performance is discussed.

To participate: University of Genoa Teams group number 1npbr0h (if you have a Teams Unige account, you can access with the code. If you only have an INFN Teams account, write to simone.marzani@ge.infn.it to be added as a guest).