Person

Anna Mascellani

This person is no longer with EPFL

Official source

https://people.epfl.ch/anna.mascellani

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https://people.epfl.ch/anna.mascellani

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Related publications (166)

Please note that this is not a complete list of this person’s publications. It includes only semantically relevant works. For a full list, please refer to Infoscience.

Search for Heavy Neutral Resonances Decaying to Tau Lepton Pairs in Proton-proton Collisions at √s=13 Tev

Anna Mascellani, Joanna Malgorzata Wanczyk, Jan Steggemann, Konstantin Androsov

A search for heavy neutral gauge bosons (Z ') decaying into a pair of tau leptons is performed in proton-proton collisions at root s = 13 TeV at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of 138 f ...

AMER PHYSICAL SOC2025

Proton reconstruction with the TOTEM Roman pot detectors for high-β∗ LHC data

Anna Mascellani, Joanna Malgorzata Wanczyk, Jan Steggemann, Konstantin Androsov

The TOTEM Roman pot detectors are used to reconstruct the transverse momentum of scattered protons and to estimate the transverse location of the primary interaction. This paper presents new methods of track reconstruction, measurements of strip-level dete ...

2025

Measurements of Inclusive and Differential Cross Sections for Top Quark Production in Association with a Z Boson in Proton-proton Collisions at √s=13 Tev

Anna Mascellani, Joanna Malgorzata Wanczyk, Jan Steggemann, Konstantin Androsov

Measurements are presented of inclusive and differential cross sections for Z boson associated production of top quark pairs (t (t) over barZ) and single top quarks (tZq or tWZ). The data were recorded in proton-proton collisions at a center-of-mass energy ...

SPRINGER2025

People doing similar research (32)

Roberto Castello is a senior scientist and group leader at the EPFL Laboratory of Solar Energy and Building Physics. Physicist by training, he has extensive experience in collecting, classifying and interpreting large datasets using advanced data mining techniques and statistical methods. He received his MSc (2007) in Particle Physics and PhD (2010) in Physics and Astrophysics from the University of Torino. He worked as a postdoctoral researcher at the Belgian National Research Fund (2011-2014) and at the CERN Experimental Physics Department (2015-2017) as a research fellow and data scientist. He is primary author of more than 20 peer-reviewed publications and he presented at major international conferences in the high energy physics domain. In 2018 he joined the Solar Energy and Building Physics Laboratory (LESO-PB) to work on data mining and Machine Learning techniques for the built environment and renewable energy. His main research interests are: spatio-temporal modeling of renewable energy potential, energy consumption forecasting techniques, anomaly detection, and computer vision techniques for automated classification in the built environment. He leads the group of Urban Data Mining, Intelligence and Simulation at LESO-PB and he is a member of the NRP75 Big Data project (HyEnergy) of the Swiss National Science Foundation. He is a member of the Swiss Competence Centre for Energy Research (SCCER) and deputy leader of the working group on Leveraging Ubiquitous Energy Data. He has served as a scientific committee member, workshop organizer and speaker at international conferences (ICAE 2020, Applied Machine Learning Days 2019 and 2020, CISBAT 2019 and 2021 and SDS2020). Since 2017 he is member of the Geneva 2030 Ecosystem network, promoting the United Nations agenda towards the realization of the Sustainable Development Goals (SDGs).

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People doing similar research (32)