12th Presentation | Machine Learning techniques in Neutrino Experiments | Evangelia Drakopoulou

You can watch presentation’s recording here!

NanoAI welcomes Evangelia Drakopoulou who will present her work, titled “Machine Learning techniques in Neutrino Experiments”.

As always, an open discussion will follow.

When? January 19th, 15:30 Greece

Description: Machine Learning techniques have gained ground in particle physics for the efficient way of solving problems. In this talk I will discuss the machine learning-based methods developed by the astroparticle group of the Institute of Nuclear and Particle Physics for the neutrino experiments KM3NeT and ANNIE. KM3NeT is a research infrastructure housing the next generation neutrino telescopes: ARCA and ORCA. Located in the deepest seas of the Mediterranean, KM3NeT will search for neutrinos from distant astrophysical sources and study their properties. ANNIE is a smaller neutrino detector installed in the Booster Neutrino beam at Fermilab aiming to measure the neutron abundance in the final state of neutrino-nucleus interactions. This measurement will have a direct impact on our understanding of neutrino interactions and could lead to improvements in signal-background discrimination for future neutrino detectors. In this talk I will describe the Machine and Deep Learning methods focusing on the improvement of the detectors performance.

Evangelia Drakopoulou is an experimental particle physicist and Researcher (Grade C) at the N.C.S.R. Demokritos. Her research is focused on measuring the properties of neutrinos, subatomic particles that rarely interact with matter and on studying neutrinos flux to the Earth from astrophysical sources. She obtained a Ph.D. in Particle Physics from the National Technical University of Athens developing a Machine Learning-based method to estimate the neutrino energy in KM3NeT; a neutrino telescope in Mediterranean. Then, she was appointed as a postdoctoral fellow by the University of Edinburgh where she led studies for the optimisation of the Hyper-Kamiokande experiment in Japan and for the event reconstruction using Machine and Deep Learning techniques for the ANNIE experiment in Fermilab, USA. She joined the astroparticle physics group of INPP, Demokritos in 2021 and works for ANNIE and KM3NeT experiments.

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