Big Data Science in Astroparticle Research - Workshop

Name: Big Data Science in Astroparticle Research - Workshop
Start: 2020-02-17T13:00:00+01:00
End: 2020-02-19T14:00:00+01:00
Location: RWTH Aachen University SuperC

Feb 17, 2020, 1:00 PM → Feb 19, 2020, 2:00 PM Europe/Berlin

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

Surveys

Big Data Science in Astroparticle Research - Evaluation

contact

hap-workshop@physik.rwth-aachen.de

0241 8027330

Monday, February 17
- Arrive
- Beginners Tutorial Ford-Room: Deep Learning
  - 1
    
    Short Welcome
    
    Speaker: Martin Erdmann (RWTH Aachen University)
    
    Introduction.pdf
  - 2
    
    Deep Learning for Newcomers: Neural Network Basics
    
    Speaker: Peter Fackeldey (III. Physikalisches Institut A, RWTH Aachen University)
    
    BasicDeepLearningTutorial2020.pdf
- Tutorial: Generali Room: Advanced Deep Networks
  - 3
    
    Graph Networks Tutorial
    
    Speaker: Jonas Glombitza (RWTH Aachen University)
    
    Graph_network_tutorial.pdf
- Coffee
- Beginners Tutorial Ford-Room: Deep Learning
  - 4
    
    Deep Learning for Newcomers: Neural Network Architectures
    
    Speaker: Peter Fackeldey (III. Physikalisches Institut A, RWTH Aachen University)
    
    BasicDeepLearningTutorial2020.pdf
- Tutorial: Generali Room: Advanced Deep Networks
  - 5
    
    Graph Networks Tutorial
    
    Speaker: Jonas Glombitza (RWTH Aachen University)
    
    Graph_network_tutorial.pdf
Tuesday, February 18
- Big Data Science in Fundamental Physics Research: Perspectives of Big Data Science
  - 6
    
    Welcome to the RWTH Aachen University
    
    Speaker: Prof. Carsten Honerkamp
  - 7
    
    ErUM-Data: Modern Digitization in Research on Universe and Matter
    
    Speaker: Prof. Thomas Kuhr (LMU Munich)
    
    BigDataAachen0320.pdf
- Deep Learning
  - 8
    
    Applying Dynamic Graph CNN to reconstruct the direction of electrons in JUNO
    
    Speaker: Mr Hauke Schmidt (Hamburg)
    
    HAP2020_Hauke_Schmidt.pdf
  - 9
    
    Identification of Cosmic Rays from Sources using Dynamic Graph Convolutional Neural Networks
    
    Speaker: Mr Niklas Langner (RWTH Aachen University)
    
    HAP2020_Langner.pdf
- Coffee
- Deep Learning
  - 10
    
    FPGA Belle II Trigger
    
    Speaker: Mr Steffen Bähr (KIT)
    
    20200218_baehr_bigdata.pdf
  - 11
    
    FPGA Trigger of SuperCDMS
    
    Speaker: Dr Hanno Meyer zu Theenhausen (DESY)
    
    SuperCdmsFpgaTrigger.pdf
  - 12
    
    Xmax Reconstruction with AugerPrime using Deep Learning
    
    Speaker: Sonja Schröder (Bergische Universtität Wuppertal)
    
    Xmax_AugerPrime_Schroeder.pdf
  - 13
    
    1) Lowering the threshold of Tunka-Rex with autoencoder; 2) Toward Tunka-Rex Virtual Observatory
    
    Speaker: Dmitriy Kostunin (DESY)
    
    kostunin-dl-bd-tunkarex.pdf
- Lunch
- Deep Learning
  - 14
    
    Bayesian Networks (exact title & title tbc)
    
    Speaker: Prof. Tilman Plehn (University Heidelberg)
    
    aachen_20_Plehn.pdf
  - 15
    
    Exploitation of Symmetries and prior Knowledge in Deep Learning Architectures for IceCube
    
    Speaker: Mirco Huennefeld (TU Dortmund)
    
    2020_02_18_HAP_Aachen.pdf
  - 16
    
    Addressing domain adaptation issues with CRNNs and VERITAS data
    
    Speaker: Mr Samuel Spencer (University of Oxford)
    
    Aachen ML.pdf
- Coffee
- Deep Learning
  - 17
    
    Modern Machine Learning in Astronomy (exact title & title tbc)
    
    Speaker: Dr Kai Polsterer (HITS Heidelberg)
    
    2020_Aachen_Polsterer.pdf
  - 18
    
    Determining the distribution of interstellar gas with information field theory
    
    Speaker: Dr Andrea Vittino (RWTH Aachen University)
    
    vittino_BigDataInAstroparticle.pdf
  - 19
    
    Searching Pulsars Using Neural Networks
    
    Speaker: Mr Lars Künkel (University Bielefeld)
    
    lkuenkel_aachen.pdf
  - 20
    
    The Astrophysical Multimessenger Observatory Network (AMON)
    
    Speaker: Prof. Miguel Mostafa (Penn State University)
    
    AMON-colloquium-BigData.pdf
- Conference Dinner
Wednesday, February 19
- Deep Learning
  - 21
    
    Simulation of Extensive Air Showers with Deep Neural Networks
    
    Speaker: Marcel Köpke (Karlsruhe Institute of Technology)
    
    koepke.pdf
  - 22
    
    Physics motivated GAN for generating fourmomenta
    
    Speaker: Mr Niclas Eich (RWTH Aachen University)
    
    EichHAPWorkshop2020.pdf
- Open Data, Data Centers, Computing Technology
  - 23
    
    The Astro@NFDI Endevour
    
    Speaker: Dr Harry Enke (Leibniz-Institut für Astrophysik Potsdam (AIP))
    
    Astro-NFDI-endeavour.pdf
  - 24
    
    Open data and machine learning in German--Russian Data Life Cycle initiative
    
    Speaker: Victoria Tokareva (KIT)
    
    pres_HAP_20_tokareva_1.pdf
- Coffee
- Open Data, Data Centers, Computing Technology
  - 25
    
    Particle & Astroparticle Physics @ NFDI
    
    Speaker: Andreas Haungs (KIT)
    
    NFDI-HAP-Aachen-Feb2020-Haungs.pdf
- Discussion on perspectives and common efforts
  
  discussion-v3.pdf
- Depart

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Big Data Science in Astroparticle Research - Workshop

RWTH Aachen University SuperC

Helmholtz Alliance for Astroparticle Physics HAP Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz der Deutschen Physikalischen Gesellschaft e. V. AKPIK

Helmholtz Alliance for Astroparticle Physics HAP

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