Big Data Science in Astroparticle Research - HAP Workshop

Feb 19, 2018, 1:00 PM → Feb 21, 2018, 3:00 PM Europe/Berlin

RWTH Aachen University SuperC

Andreas Haungs (KIT), Martin Erdmann

Poster High-res (20 MB) https://indico.scc.kit.edu/indico/event/344/picture/10.pdf

Poster Low-res Poster Low-res

Monday, February 19

Arrive

Deep Learning

1 Welcome and organizational matters

Speaker: Prof. Martin Erdmann (RWTH Aachen University)

Slides Introduction.pdf

2 Tutorial Deep Networks: Introduction, Fully-Connected, Convolutional Architectures

Speaker: Mr Yannik Rath (RWTH Aachen University)

Slides Tutorial_HAP_Workshop_PartI.pdf

Coffee

Deep Learning

3 Tutorial on Adversarial Generative Networks, Wasserstein distance

Speaker: Mr Jonas Glombitza (RWTH Aachen University)

Slides GAN_tutorial_hap_workshop.pdf

Tuesday, February 20

Deep Learning

4 Welcome Message of the Vice-Rector for Research and Structure

Speaker: Prof. Rudolf Mathar (RWTH Aachen University)

5 DeepJet: jet classification with the CMS experiment

Speaker: Dr Markus Stoye (CERN)

Slides BigAstroAachen.pdf

6 Application of machine learning methods to H.E.S.S. data analysis

Speaker: Dr Idan Shilon (ECAP University Erlangen)

Slides Shilon_GNN.pdf

7 Event Reconstruction in IceCube using Deep Learning Techniques

Speaker: Mr Mirco Huennefeld (TU Dortmund)

Slides 2018_02_20_Aachen_HAP.pdf

Coffee

Deep Learning

8 Efficient Similarity Search and Analysis

Speaker: Dr Christian Beecks

Slides Beecks_Efficient_Similarity_Search_and_Analysis.pdf

9 Generating and refining particle detector simulations using the Wasserstein distance in adversarial networks

Speaker: Mr Lukas Geiger (RWTH Aachen University)

Slides lgeiger-slides.pdf

10 HexagDLy - Hexagonal Convolutions with PyTorch

Speaker: Mr Tim Lukas Holch (Humboldt University Berlin)

Slides tlholch_hexagdly_hap_2018.pdf

11 Deep machine learning implementation in FPGA

Speakers: Dr Michele Caselle (KIT), Mr Weijia WANG

Slides ML_FPGA_Caselle.pdf

Lunch

Deep Learning

12 Making Deep Neural Networks Transparent

Speaker: Dr Wojciech Samek (Fraunhofer Heinrich Hertz Institute Berlin)

Slides Talk_Samek.pdf

13 Denoising radio traces with autoencoder on Tunka-Rex experiment

Speaker: Dr Dmitriy Kostunin (IKP KIT Karlsruhe)

Slides kostunin-hap-big-data-2018.pdf

14 Deep Neural Network searching for an air shower radio signal

Speaker: Radomir Smida (Karlsruhe Institute of Technology (KIT))

Slides Smida-DNN-20180220.pdf

Coffee

Deep Learning: 1-2 Transparencies

15 Investigating deep convolutional autoencoders to mitigate systematic differences between data and simulations

Speaker: Dr Stefan Geißelsöder (ECAP, FAU Erlangen)

Slides 201802_ECAP_Autoencoder_Aachen.pdf

16 Using Deep Learning to optimise a SUSY search at CMS

Speaker: Dr Adam Elwood (DESY Hamburg)

Slides Elwood_SUSY_Aachen.pdf

Open Data, Data Centers, Computing Technology

17 Introduction to Open Data

Speaker: Prof. Uli Katz (ECAP / Univ. Erlangen)

Slides aachen_bigdata_1802.pdf

18 FACT Open Data Release

Speaker: Mr Maximilian Nöthe (Herr)

Slides fact_open_data.pdf

Conference Dinner

Wednesday, February 21

Open Data, Data Centers, Computing Technology

19 Research Data Alliance

Speaker: Dr Peter Wittenburg (Max Planck Institute for Psycholinguistics Nijmegen, NL)

Slides peter-rwth-talk.pdf

20 Big scientific data and Data Science

Speaker: Prof. Tony Hey (Rutherford Appleton Laboratory, UK)

Slides Tony_Hey_-_Big_Scientific_Data_and_Data_Science__-_Aachen_(Feb_18).pdf

Coffee

Open Data, Data Centers, Computing Technology

21 Progress on analysis and data centre for astroparticle physics

Speaker: Dr Andreas Haungs (KIT)

Slides BigData-HAP-Aachen-Feb2018-Haungs.pdf

22 Concrete goals for (Astro-)particle progress related to Big Data Science

Speaker: Prof. Alexander Schmidt (RWTH Aachen University)

Slides talkAachenFeb2018.pdf

Discussion on perspectives and common efforts

23 Discussion

Speakers: Dr Andreas Haungs (KIT), Prof. Martin Erdmann (RWTH Aachen University)

Slides Discussion.pdf

Depart