LIP | Events Platform

School   25, 26, 27 MARCH 2019



Mornings:
Lectures by Glen Cowan and Tommaso Dorigo

1. Probability & Statistics
2. Machine Learning

AGENDA   TIMETABLE (w/ school materials)

Elena Cuoco - lectures gravitational waves

 

Afternoons:
Hands On - Tutorials and data challenge
The Data challenge will be a classification problem using gravitational waves data.

Agata Trovato - hands-on
Filip Morawski - hands-on
Giles Strong - tutorial on modern machine learning tools
Roberto Corizzo - hands-on
Elena Cuoco - data challenge
Massimiliano Razzano - data challenge

Tiago Vale - support to the data challenge


descriptionsoftware instructions:
https://lip-computing.github.io/datascience2019

1. Probability & Statistics - Lorenzo Cazon, Ruben Conceição, Felix Riehn, Bernardo Tomé
2. Machine Learning - Guilherme Milhano, Nuno Castro, Giles Strong, Celso Franco, Rute Pedro, Mário David


Lecturers

The panel is composed by LIP resident lecturers and invited lecturers coming from CERN, and from other institutes.

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Glen Cowan

Professor of Physics at Royal Holloway, University of London.
Coordinator and developer of statistical methods in ATLAS, (CERN).
Author of the book "Statistical Data Analysis".
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Tommaso Dorigo

Experimental particle physicist, who works for the INFN at the University of Padova, and collaborates with the CMS experiment at the CERN LHC. He coordinates the European network AMVA4NewPhysics as well as research in accelerator-based physics for INFN-Padova.
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Elena Cuoco

Head of Data Science Office at European Gravitational Observatory (EGO) and Associate Faculty at Scuola Normale Superiore (Pisa). Expert in noise analysis and system identification and machine learning pipeline. Member of LIGO/Virgo collaboration. CA17137 Action chair (www.g2net.eu).
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Massimiliano Razzano

Researcher at the Department of Physics of the University of Pisa. His main research interests are in gravitational wave physics and astroparticle physics, with a special focus on advanced data analysis techniques including deep learning. Member of LIGO/Virgo collaboration. CA17137 Action Member (www.g2net.eu).

SPONSORS

WORKSHOP

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