Cours
PHYS-815: 7th Machine learning in HEP Summer School
Résumé
The school will cover the relatively young area of data analysis and computational research that has started to emerge in High Energy Physics (HEP). It is known by several names including "Multivariate Analysis", "Neural Networks", "Classification/Clusterization techniques"
Source officielle
Page Moodle
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Enseignant
Magalí Alejandra Lingenfelder
Magalí Lingenfelder is currently leading the Max Planck-EPFL Laboratory for Molecular Nanoscience. Her vision is to create atomically tailored interfaces for applications in two distinct areas of urgent technological and societal relevance: energy conversion and smart antimicrobial interfaces. To access the nanoscale, her group uses a combination of state-of-the-art scanning probe microscopy and solid state spectroscopy, allowing the study of kinetic processes in-situ under liquid flow and potential control conditions (operando electrocatalysis). She made seminal contributions to the field of metal-organic coordination networks on solid surfaces, and received the Otto Hahn medal in 2008 for the microscopic understanding of the chiral recognition process with submolecular resolution. She is a committed mentor, and since her relocation from the Lawrence Berkeley National Laboratory, USA to EPFL in 2013, she directed 3 MSc. theses, 4 PhD theses and 4 postdocs. She advocates for problem-oriented interdisciplinary research: she led 5 international research consortiums, delivered over 40 invited presentations and organized 9 conferences and 4 doctoral schools. In 2018, the Royal Society of Chemistry included her work in the first collection “Celebrating Excellence in Research: 100 Women of Chemistry”.
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