1. DOE Review Jean-Roch Vlimant

2. 2011 CMS Achievement Award
For “excellent work in the Reconstruction project as convener as well as in the daily offline operation”.

3. 2014 CMS Young Researcher Prize
For “his sustained and critical contributions to the development of software for the calorimeter and tracking triggers at HLT ; data quality monitoring, detector simulation and reconstruction software”.

4. Roles in CMS
Convener of the Physics Data Monte-Carlo Validation group (2012/13). Expediting central production of data and simulation samples. Design and development of validation book-keeping tools and procedures. Design and development of production preparation, submission and book-keeping software.
2011 CMS Achievement Award
Convener of the Offline Reconstruction group (2010/2011). Development, tutoring, maintenance and managment of the offline reconstruction software. Contributions to high level trigger software. Sole developer of the cms sofware configuration builder.
Coordinator of the muon high level trigger (2009/2008). Development of the muon trigger and monitoring. Contributions to online Ecal and tracker local reconstruction.
Coordinator of tracking software group (2009). Development, maintenance and management of tracking software.

5. Recent Activities 2014 CMS Young Researcher Prize
Maintenance of Monte-Carlo Management platform (McM). Development and commissioning of new procedures to expedite production.
Analysis of jet substructure in search for “X to ZH” signatures.
Analysis of razor variables with 13 TeV simulation.
Development of book-keeping service for production of analysis samples.
Automation of computing operation for central production service resulting in shorter delays in preparation of samples for analysis
Research Machine Learning Techniques for applications to CMS challenges.

6. X to ZH with Jet Substructure
Hashed ≡
background
Colored ≡
signal
Discrimination method
– τ1
– τ2
– τ3
– τ2/τ1
– τ3/τ2
– τ3/τ1
– MLPBNN
– LPCA
Separation significance
Arbitrary unit
Cut on discriminant
MLPBNN value
MLPBNN : neurla network with BFGS training method and bayesian regulator
LPCA : 1-dimensional likelihood with PCA-transformed input variables
Search for heavy exotic particle X→ZH→2 lepton, 4 quarks where quarks hadronize in highly collimated jets. The four-pole structure of the resulting fat-jet is discriminated from background jets using n-subjetiness (tauN) and multivariate analysis techniques.

7. Machine Learning Signal Extraction
INPUT pseudo-data with signal injected
OUTPUT
categorization exhibiting unknown events
log(MR)
Self-Organizing-Map trained on pseudo-data and interpreted with known backgrounds
log(MR)
Unsupervised clustering (self-organizing map : SOM, kMean, principal component analysis, correlation explanation, ... ) of pseudo-data towards supervised categorization of event populations and identification/discovery of unknown signal.

8. Complex Model Deep Learning R&D
Tracking : Rely on ability to learn complex models. Learn from hit pattern of charged particle for track reconstruction.
Jet substructure : Apply image recognition technique to classification of energy-flow particle 4-momentum patterns.

9. Data Science Workshop Organization
Hands-on oriented workshop with presentation of contemporary machine learning techniques to foster.

10. Computing Operation Automation
Fully automatize handling of production requests
Pre-defined simple rules of placement
Automation of sanity check and final delivery
Amount of operator work reduced
Possible to handle smoothly more resource

11. Computing Operation Performance
Great current total through-put
~250M/week +
~500M/week
Delays of delivery to analysis much reduced
Jean-Roch's
automation

12. Computing Optimization R&D
Computing WW grid
Applied
Global monitoring
Modify assignment
Time to completion
Learn complex models using deep learning from monitoring and metric. Use models in intensive simulation within application of game theory techniques or reinforcement learning method. Steering computing, storage and network elements like robot arms.