Workshop on Machine Learning for Cosmic-Ray Air Showers
from
Monday, January 31, 2022 (5:00 PM)
to
Thursday, February 3, 2022 (5:30 PM)
Monday, January 31, 2022
5:00 PM
5:00 PM - 5:30 PM
5:30 PM
5:30 PM - 7:00 PM
Tuesday, February 1, 2022
9:00 AM
Welcome
Welcome
9:00 AM - 9:15 AM
9:15 AM
9:15 AM - 10:30 AM
Contributions
9:15 AM
Deep learning in astroparticle physics
-
Jonas Glombitza
(
RWTH AACHEN UNIVERSITY
)
10:00 AM
Machine Learning for High-Energy Physics Reconstruction and Analysis
-
Sergei Gleyzer
10:30 AM
Coffee Break
Coffee Break
10:30 AM - 11:00 AM
11:00 AM
11:00 AM - 12:30 PM
Contributions
11:00 AM
Exploitation of Symmetries and Domain Knowledge in Deep Learning Architectures
-
Mirco Huennefeld
(
Universität Dortmund
)
11:45 AM
Composition Analysis of cosmic-rays at IceCube Observatory, using Graph Neural Networks
-
Paras Koundal
(
Karlsruhe Institute of Technology
)
12:30 PM
Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM
Tuesday
Tuesday
2:00 PM - 3:30 PM
Contributions
2:00 PM
Measurement of the high-energy muon multiplicity in cosmic-ray air showers with IceTop and IceCube using neural networks
-
Stef Verpoest
(
University of Gent
)
2:30 PM
Air shower reconstruction using a Graph Neural Network for the IceAct telescopes
-
Larissa Paul
(
Marquette University
)
3:00 PM
Cosmic ray mass composition study using a Random Forest applied to data from the IceAct telescopes
-
Larissa Paul
(
Marquette University
)
3:15 PM
Pattern Recognition for Multiple Interactions in a Neutron Monitor
-
P.-S. Mangeard
(
University of Delaware
)
3:30 PM
Coffee Break
Coffee Break
3:30 PM - 4:00 PM
4:00 PM
Tuesday
Tuesday
4:00 PM - 5:30 PM
Contributions
4:00 PM
Composition of 100 TeV - 100 PeV Cosmic Rays with IceCube and IceTop using Boosted Decision Trees
-
Julian Saffer
(
Karlsruhe Institute of Technology
)
4:30 PM
Cosmic rays primary energy estimation using Machine Learning and combined reconstruction
-
Diana Leon Silverio
(
South Dakota School of Mines and Technology
)
5:00 PM
Energy Reconstruction with Convolutional Neural Networks in IceTop
-
Frank McNally
(
Mercer University
)
Wednesday, February 2, 2022
9:00 AM
9:00 AM - 10:30 AM
Contributions
9:00 AM
Machine learning based event reconstruction in Telescope Array surface detector
-
Oleg Kalashev
(
INR RAS Moscow
)
9:45 AM
State-of-art deep learning technologies and their application to air-shower reconstruction
-
Vladimir Sotnikov
(
JetBrains Research
)
10:30 AM
Coffee Break
Coffee Break
10:30 AM - 11:00 AM
11:00 AM
11:00 AM - 12:30 PM
Contributions
11:00 AM
Deep Learning for Air Shower Reconstruction at the Pierre Auger Observatory
-
Jonas Glombitza
(
RWTH AACHEN UNIVERSITY
)
for the Pierre Auger Collaboration
11:30 AM
Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks
-
Juan Miguel Carceller
(
University College London
)
12:00 PM
Neural Network Approaches for Event Classification Onboard EUSO-SPB2
-
George Filippatos
(
Colorado School of Mines
)
12:30 PM
Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM
2:00 PM - 3:30 PM
Contributions
2:00 PM
CORSIKA and CONEX for air shower simulations
-
Tanguy Pierog
(
Karlsruhe Institute of Technology (KIT), IAP
)
2:45 PM
CORSIKA 8: A modern framework for high-energy cascade simulations
-
Remy Prechelt
(
University of Hawai'i
)
3:30 PM
Coffee Break
Coffee Break
3:30 PM - 4:00 PM
4:00 PM
Tutorial
Tutorial
4:00 PM - 5:30 PM
Contributions
4:00 PM
Machine Learning and Artificial Intelligence in Physics: Overview and Applications
-
Gregory Dobler
(
University of Delaware
)
Thursday, February 3, 2022
9:00 AM
9:00 AM - 10:30 AM
Contributions
9:00 AM
Machine learning in Baikal-GVD
-
Ivan Kharuk
(
Institute for Nuclear Research RAS
)
9:35 AM
Towards mass composition study with KASCADE using deep learning
-
Daniil Reutsky
(
Moscow Institute of Physics and Technology
)
9:55 AM
IACT event reconstruction with deep learning: some progress, lessons learned, and outlook from CTLearn
-
Daniel Nieto
(
Instituto de Física de Partículas y del Cosmos and Departamento de EMFTEL, Universidad Complutense de Madrid
)
10:30 AM
Coffee Break
Coffee Break
10:30 AM - 11:00 AM
11:00 AM
11:00 AM - 12:30 PM
Contributions
11:00 AM
Search for optimal deep neural network architecture for gamma detection at KASCADE
-
Margarita Tsobenko
(
Higher School of Economics University - St. Petersburg
)
11:20 AM
Photon flux calculation using Deep Learning
-
Jigar Bhanderi
11:55 AM
Improving the gamma-hadron separation for air showers at the IceCube Neutrino Observatory
-
Federico Bontempo
(
Karlsruhe Institute of Technology
)
12:30 PM
Lunch
Lunch
12:30 PM - 2:00 PM
2:00 PM
2:00 PM - 3:30 PM
Contributions
2:00 PM
Open questions in deep learning techniques for the radio detection
-
Dmitriy Kostunin
(
DESY
)
2:45 PM
Deep Learning for Classification and Denoising of Cosmic-Ray Radio Signals
-
Abdul Rehman
(
University of Delaware
)
3:15 PM
Training Neural Networks to Classify and Denoise Cosmic-Ray Radio Signals Using Background Measured at the South Pole
-
Dana Kullgren
(
University of Delaware
)
3:30 PM
Coffee Break
Coffee Break
3:30 PM - 4:00 PM
4:00 PM
4:00 PM - 5:30 PM
Contributions
4:00 PM
Crowdsourcing your training labels with Zooniverse
-
Lucy Fortson
(
University of Minnesota
)
4:30 PM
What slow down cosmic ray analysis and what can we do about them?
-
Xinhua Bai
(
South Dakota School of Mines and Technology
)
4:55 PM
Workshop on Machine learning for Cosmic-Ray Air Showers - Summary & Outlook
-
Matthias Plum
(
Marquette University
)
5:20 PM
Good Bye
-
Frank Schroeder
(
University of Delaware / Karlsruhe Institute of Technology
)