Big Data Science in Astroparticle Research - Workshop

Europe/Berlin
RWTH Aachen University SuperC

RWTH Aachen University SuperC

RWTH Aachen University Templergraben 57, 52062 Aachen phone:0241 8090801
Andreas Haungs (KIT), Martin Erdmann
Description

Helmholtz Alliance for Astroparticle Physics HAP

Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz der Deutschen Physikalischen Gesellschaft e. V. AKPIK


Castle Erlangen (© Erich Malter)

Surveys
Big Data Science in Astroparticle Research - Evaluation
    • 13:00 14:00
      Arrive
    • 14:00 15:45
      Beginners Tutorial Ford-Room: Deep Learning
      • 14:00
        Short Welcome 10m
        Speaker: Martin Erdmann (RWTH Aachen University)
      • 14:10
        Deep Learning for Newcomers: Neural Network Basics 1h 30m
        Speaker: Peter Fackeldey (III. Physikalisches Institut A, RWTH Aachen University)
    • 14:00 15:45
      Tutorial: Generali Room: Advanced Deep Networks
    • 15:45 16:15
      Coffee
    • 16:15 17:15
      Beginners Tutorial Ford-Room: Deep Learning
      • 16:15
        Deep Learning for Newcomers: Neural Network Architectures 1h
        Speaker: Peter Fackeldey (III. Physikalisches Institut A, RWTH Aachen University)
    • 16:15 18:00
      Tutorial: Generali Room: Advanced Deep Networks
    • 09:00 10:00
      Big Data Science in Fundamental Physics Research: Perspectives of Big Data Science
      • 09:00
        Welcome to the RWTH Aachen University 20m
        Speaker: Prof. Carsten Honerkamp
      • 09:20
        ErUM-Data: Modern Digitization in Research on Universe and Matter 40m
        Speaker: Prof. Thomas Kuhr (LMU Munich)
    • 10:00 10:40
      Deep Learning
      • 10:00
        Applying Dynamic Graph CNN to reconstruct the direction of electrons in JUNO 20m
        Speaker: Mr. Hauke Schmidt (Hamburg)
      • 10:20
        Identification of Cosmic Rays from Sources using Dynamic Graph Convolutional Neural Networks 20m
        Speaker: Mr. Niklas Langner (RWTH Aachen University)
    • 10:40 11:10
      Coffee
    • 11:10 13:00
      Deep Learning
    • 13:00 14:30
      Lunch
    • 14:30 15:50
      Deep Learning
      • 14:30
        Bayesian Networks (exact title & title tbc) 40m
        Speaker: Prof. Tilman Plehn (University Heidelberg)
      • 15:10
        Exploitation of Symmetries and prior Knowledge in Deep Learning Architectures for IceCube 20m
        Speaker: Mirco Huennefeld (TU Dortmund)
      • 15:30
        Addressing domain adaptation issues with CRNNs and VERITAS data 20m
        Speaker: Mr. Samuel Spencer (University of Oxford)
    • 15:50 16:20
      Coffee
    • 16:20 18:00
      Deep Learning
      • 16:20
        Modern Machine Learning in Astronomy (exact title & title tbc) 40m
        Speaker: Dr. Kai Polsterer (HITS Heidelberg)
      • 17:00
        Determining the distribution of interstellar gas with information field theory 20m
        Speaker: Dr. Andrea Vittino (RWTH Aachen University)
      • 17:20
        Searching Pulsars Using Neural Networks 20m
        Speaker: Mr. Lars Künkel (University Bielefeld)
      • 17:40
        The Astrophysical Multimessenger Observatory Network (AMON) 20m
        Speaker: Prof. Miguel Mostafa (Penn State University)
    • 19:00 22:00
      Conference Dinner
    • 09:00 09:40
      Deep Learning
      • 09:00
        Simulation of Extensive Air Showers with Deep Neural Networks 20m
        Speaker: Marcel Köpke (Karlsruhe Institute of Technology)
      • 09:20
        Physics motivated GAN for generating fourmomenta 20m
        Speaker: Mr. Niclas Eich (RWTH Aachen University)
    • 09:40 10:40
      Open Data, Data Centers, Computing Technology
      • 09:40
        The Astro@NFDI Endevour 40m
        Speaker: Dr. Harry Enke (Leibniz-Institut für Astrophysik Potsdam (AIP))
      • 10:20
        Open data and machine learning in German--Russian Data Life Cycle initiative 20m
        Speaker: Victoria Tokareva (KIT)
    • 10:40 11:10
      Coffee
    • 11:10 11:50
      Open Data, Data Centers, Computing Technology
    • 11:50 13:00
      Discussion on perspectives and common efforts
    • 13:00 14:00
      Depart
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