Name: IWAPP - Innovative Workflows in Astro- & Particle Physics
Start: 2021-03-08T10:00:00+01:00
End: 2021-03-12T13:00:00+01:00
Location: Online

IWAPP - Innovative Workflows in Astro- & Particle Physics

de lundi 8 mars 2021 (10:00) à vendredi 12 mars 2021 (13:00)

lundi 8 mars 2021
10:00 Overview presentations
Overview presentations
10:00 - 12:45
Contributions

10:00 Introduction & Overview - Elena Cuoco

10:10 OSSR & ESCAPE - Kay Graf (ECAP - University of Erlangen)

10:20 Technical introduction - Jutta Schnabel (FAU Erlangen (ECAP))

10:30 AI at scale - Giuseppe Fiameni (NVIDIA)

11:45 Deep Learning for real-time data processing at the LHC - Maurizio Pierini (CERN)
15:00 Bring your own container - open interactive session
Bring your own container - open interactive session
15:00 - 17:00
Contributions

15:00 Astro-COLIBRI: a new platform for time-domain astronomy - Fabian Schussler (CEA/Irfu)

15:00 Virtual Observatory - Hendrik Heinl (CDS/ObAS)
mardi 9 mars 2021
09:30 Specific approaches
Specific approaches
09:30 - 12:45
Contributions

09:30 MEGAVIS - Real-time spectra analysis and visualization with autoencoders - Antonio D'Isanto (HITS gGmbH)

10:00 APEIRON - Luca Pontisso Matteo Turisini (INFN)

10:30 Real-time analysis in high energy physics and beyond - Caterina Doglioni (Lund University)

11:15 Some benefits of using normalizing flows for PDF modelling - Thorsten Glüßenkamp

11:45 A machine learning workflow for reproducible data science - Luca Antiga
15:00 Plenary
Plenary
15:00 - 16:30
Contributions

15:00 Hands-on data-versioning for scientific pipelines with Hangar - Alberto Iess (INFN Roma Tor Vergata) Filippo Quarenghi (Orobix)

16:00 Using normalizing flows - Thorsten Glüßenkamp
mercredi 10 mars 2021
09:30 Solutions in Research Infrastructures
Solutions in Research Infrastructures
09:30 - 12:30
Contributions

09:30 Machine Learning Algorithms in LIGO-Virgo - Maxime Fays

10:00 Anomaly Detection in Gravitational Waves data using Convolutional AutoEncoders - Filip Morawski (Nicolaus Copernicus Astronomical Center of the Polish Academy of Sciences)

10:20 Science data challenges for the SKA - Alex Clarke

11:10 Machine Learning Workflows in KM3NeT - Stefan Reck (ECAP - University of Erlangen)

11:40 Incorporating deep learning into the analysis of the Cherenkov Telescope Array - Tjark Miener

12:10 GNA: data flow approach for the neutrino oscillation experiments - Maxim Gonchar (JINR) Maxim Gonchar (JINR)
14:00 Open interactive session
Open interactive session
14:00 - 16:00
Contributions

14:00 The OSSR - Jutta Schnabel (FAU Erlangen (ECAP))

14:00 ALFA / FairRoot Framework - Dmytro Kresan (GSI)
17:00 Finding common ground
Finding common ground
17:00 - 18:00
Contributions

17:00 Machine Learning in Healthcare - Mauricio Santillana (Boston Children's Hospital / Harvard Medical School)
jeudi 11 mars 2021
09:30
09:30 - 10:00
Contributions

09:30 KM3NeT Tier-2 Computing at Tbilisi State University - Gogita Papalashvili

09:37 New approaches for multi-messenger real time analysis - Barbara Patricelli (EGO)

09:44 Classifying galaxies, quasars and stars in optical surveys with machine learning - Alex Clarke

09:51 Distributed data processing using FairMQ framework. - Dmytro Kresan (GSI)
10:00 Presentations
Presentations
10:00 - 12:00
Contributions

10:00 The test science projects as starting point for common efforts - Caterina Doglioni (Lund University) Elena Cuoco

10:50 Introduction to discussion sessions

11:10 Discussion topics overview
15:00 Discussion groups
Discussion groups
15:00 - 16:45
Contributions

15:00 Discussion 4: Workflow management for machine learning - Cristiano Bozza

15:00 Discussion 3: Machine & deep learning techniques - Luca Antiga

15:00 Discussion 2: use of alternative hardware - Maurizio Pierini (CERN)

15:00 Discussion 5: Real time analysis and triggering - Caterina Doglioni (Lund University)

15:00 Discussion 1: Data reduction and data formats - Kai Polsterer (HITS gGmbH)

16:00 Discussion 3: Machine & deep learning techniques - Luca Antiga

16:00 Discussion 1: Data reduction and data formats - Kai Polsterer (HITS gGmbH)

16:00 Discussion 4: Workflow management for machine learning - Cristiano Bozza

16:00 Discussion 5: Real time analysis and triggering - Caterina Doglioni (Lund University)

16:00 Discussion 2: use of alternative hardware - Maurizio Pierini (CERN)
vendredi 12 mars 2021
10:00 Summary & Outlook
Summary & Outlook
10:00 - 12:30
Contributions

10:00 AI and ML landscape and ideas for platforms and services by EGI - Ville Tenhunen (EGI)

10:30 Reports from the discussion groups

11:20 Panel discussion

12:20 Summary - Elena Cuoco

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