Name: Machine Learning for the LHC Distributed Data Placement and Track Finding
Start: 2015-12-07T10:00:00+03:00
End: 2015-12-09T20:00:00+03:00
Location: Other Institutes

Monday, 7 December
- 10:00 → 10:10
  
  NRC KI Welcome 10m
  
  Speaker: Vasily Velikhov (National Research Centre Kurchatov Institute (RU))
- 10:10 → 10:20
  
  Introduction and Workshop Primary Goals 10m
  
  Speakers: Alexei Klimentov (Brookhaven National Laboratory (US)), Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)), Paolo Calafiura (Lawrence Berkeley National Lab. (US))
  
  ML_Intorduction.pdf
  
  ML_Intorduction.pptx
- 10:20 → 12:30
  Machine Learning Principles, Tools and Libraries (I)
  
  Convener: Mario Lassnig (CERN)
  - 10:20
    Machine Learning hands-on 2h 10m
    
    Speakers: Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)), Dr Rogozhnikov Alexey (School of Data Analysis)
    
    Rogozhnikov-Introduction to machine learning.pdf
    
    Machine Learning Introduction 1h 20m
    
    Speaker: Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))
    
    Machine Learning for Tracking 40m
    
    Speaker: Aleksei Rogozhnikov (Yandex School of Data Analysis (RU))
- 12:30 → 13:30
  
  lunch 1h
- 13:30 → 15:10
  Machine Learning Tools, Principles and Libraries (II)
  
  Convener: Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))
  - 13:30
    
    Topological Trigger Optimization 40m
    
    Speaker: Tatiana Likhomanenko (National Research Centre Kurchatov Institute (RU))
    
    triggers.pdf
  - 14:10
    
    Flavour Tagging Optimization 1h
    
    Speakers: Denis Derkach (Yandex School of Data Analysis (RU)), Tatiana Likhomanenko (National Research Centre Kurchatov Institute (RU))
    
    tagging.pdf
- 15:10 → 15:30
  
  Tea break 20m
- 15:30 → 18:30
  Data Placement
  
  Convener: Alexei Klimentov (Brookhaven National Laboratory (US))
  - 15:30
    Data Placement Policy Evolution in ATLAS 40m
    
    Speakers: Alexei Klimentov (Brookhaven National Laboratory (US)), Mario Lassnig (CERN)
    
    ml_for_atlas_ddm.pdf
    
    Computing Model (from Monarc to "mesh")
    
    Data formats and data popularity
    
    PD2P - PanDA Dynamic Data Placement : concept and realization
    
    Rucio : Architecture overview
    
    ATLAS Data (Run1, Run2 and beyond)
    
    Sources of (data) meta-information
    
    Topics of interest
  - 16:10
    
    Data Placement and Data Handling in LHCb 40m
    
    Speakers: Andrey Ustyuzhanin (Yandex School of Data Analysis (RU)), Mikhail Hushchyn (Yandex School of Data Analysis (RU))
    
    Hushchyn_datapop_presentation.pdf
  - 17:10
    
    Data Placement simulation and Distributed Computing Simulation - round table discussion 1h 10m
- 18:30 → 19:50
  
  Bus to JINR (Dubna) 1h 20m
Tuesday, 8 December
- 10:00 → 10:10
  
  Welcome frоm LIT JINR Director 10m
  
  Speaker: Vladimir Korenkov (Joint Inst. for Nuclear Research (RU))
- 10:10 → 11:40
  
  Data Science at LHC Workshop Highlights 1h 30m
  
  Speakers: David Rousseau (LAL-Orsay, FR), Dirk Duellmann (CERN)
  
  dirkd-ml-dubna_20151208.pdf
  
  tr151208_davidRousseau_MLDubna_DSLHC2015_conclusion.pptx.pdf
  
  tr151208_davidRousseau_MLDubna_DSLHC2015_summary.pptx.pdf
- 11:40 → 12:40
  Machine Learning Tools, Principles and Libraries (III)
  - 11:40
    
    Track Finding (COMET & SHIP) 1h
    
    Speaker: Mikhail Hushchyn (Yandex School of Data Analysis (RU))
    
    Hushchyn_tracking_presentation.pdf
- 12:40 → 14:00
  
  lunch 1h 20m
- 14:00 → 14:30
  
  LHCbEventIndex - applications and possibilities 30m
  
  Speaker: Nikita Kazeev (Yandex School of Data Analysis (RU))
  
  event_index_dubna_2015.pdf
- 14:30 → 14:50
  
  ML for anomaly detection in HEP detector (LHCb) 20m
  
  Speaker: Nikita Kazeev (Yandex School of Data Analysis (RU))
  
  dubna-2015-anomalies.pdf
- 14:50 → 15:50
  
  Data-Intensive Applications on HPC Using Hadoop, Spark and RADICAL-Cybertools 1h
  
  Speaker: Prof. Shantenu Jha (Rutgers University)
  
  link to vydio conf (talk will be given remotely)
  
  slides
- 15:50 → 16:20
  ML and Distributed Computing Modeling activities at LIT JINR 30m
  
  Speaker: Prof. Ososkov Gennady (JINR)
  
  New things in wavelet analysis.pdf
  
  New things in wavelet analysis.pptx
  
  Ososkov_Pattern Recognition_ in_HEP.pdf
  
  Ososkov_Pattern Recognition_ in_HEP.pptx
  - pattern recognition in HEP
- 16:20 → 16:40
  
  tea break 20m
- 16:40 → 18:00
  
  round table discussion 1h 20m
- 19:00 → 21:30
  
  Workshop dinner
Wednesday, 9 December
- 09:30 → 12:30
  
  Data Placement and Distributed Computing Analytical Model: topical discussion about data placement for ATLAS et el Grid analytical model Deep learning tutorial (TBC) Splinter meetings
- 09:30 → 12:30
  
  Deep Learning Tutorial by Yandex (TBC)
  
  Registration form