Acknowledgements

First and foremost, I would like to thank my PhD supervisor Tommaso Dorigo for his support and guidance during the last three years. In addition to the valuable feedback that he provided on the various projects presented in this document and the much needed help with the seemingly endless bureaucratic endeavours, his advising style was consequential for finding a beneficial balance between exploration of curiosity-driven research ideas and their exploitation. Tommaso is also to blame for many improvements on my writing style as well as the blueprint of a PhD plan including a broad range of training opportunities.

Most of the analysis work within the CMS Collaboration could not have been carried out without the help and support of my postdoc officemates Martino Dall’Osso and Andres Tiko, so I would like to thank them both for their work and their friendship. The collaboration and discussions with Mia Tosi, Alexandra Oliveira and Roberto Rossin were also instrumental for the CMS analysis work. I would like also to express gratitude towards the other members of the CMS group at Padova, that were very welcoming since the beginning and regularly demonstrated interest and gave feedback on the status of my research. I would also like to acknowledge all assistance received by the administrative staff of the INFN - Sezione di Padova.

A substantial fraction of the work presented here was carried out within the CMS Collaboration, and thus was shaped by interactions with some of its thousands of members by different means including insightful comments after presentations, long e-mail discussions, and the review of diverse documents. In addition to thankfully acknowledge the contributions of all my CMS collaborators, I would like to highlight the role of the members of the CMS Higgs group and the HH subgroup in the development of the Higgs pair production analysis as well as of Markus Stoye, Mauro Verzetti, Jan Kieseler and Marcel Rieger regarding the project focussed on the integration DeepJet in the CMS software. Some conversations with Sebastien Wertz, Andre David, Gilles Louppe and Joeri Hermans were also particularly relevant to define some aspects of the work presented in this document.

Within the AMVA4NewPhysics network, which was the research community that motivated many of the research projects of my PhD, I would like to thank all the senior members for their effort in organising the various training and collaboration activities, which were important to create an open and productive research environment. Most importantly, I would like to thank the other network students (aka ESRs), which were always available for stimulating chats about research, life or the universe over coffee or beers. I would also like to express my gratitude towards Sabine Hemmer and Pietro Vischia for the energy they devoted to motivate and manage scientific outreach in the form of blogging and Twitter, which turned out to be very positive experiences.

In addition, I would like to thank Giovanna Menardi and Bruno Scarpa from the UNIPD Statisics department for hosting me for one month and providing feedback on the statistical aspects of my research. Maurizio Sanarico at SDG Consulting was also very accommodating during the months spent in Milan. Also to Daniel Whiteson, Peter Sadowski, and other attendants of the ML for HEP meeting in UCI, which gave initial support for the new machine learning technique described in this thesis. I am also thankful to Kostas Vellidis and IASA for hosting me in Athens. The environment provided by CERN both remotely and during the secondment were essential for carrying out the majority of my research so I would like to thank everyone that works to make such institution function as it does.

One achievements are nothing but the product of incremental improvements over the work, ideas and shared experiences of others, thus the present section is guaranteed to be incomplete. Hence if a conversation we had, a paper you published, a blog post you produced, a presentation you gave, a question you answered, a book you wrote or some open-source software you developed was helpful to the work presented in this thesis, I am sincerely thankful. Last from an academic perspective, I would like to acknowledge Francisco Matorras and Alexander Read for their willingness for their work as external reviewers of this thesis.

At a personal level, moving to Padova was a bit challenging so I am grateful to have been embraced by the Scambio di Lingue group and their Touch Rugby team, through which I met many new friends and provided a great social context in this marvellous city. I would like to thank my family, particularly my parents and my grandparents, for the unconditional love and support they have provided since I happen to remember. Finally, I would like to thank Ksenija, whom I met halfway through this adventure and has been a wonderful companion since, for her persistent encouragement and affection.