Organisation

The organisers are tracking algorithms experts from three major CERN experiments (ATLAS, CMS, and LHCb), associated to Machine Learning scientists.

The team comprises organisers of former successful kaggle challenges : Higgs Machine Learning challenge in 2014 ( proceedings of NIPS 2014 workshop) and Flavour of Physics challenge in 2015

David Rousseau, senior physicist at LAL-Orsay, developed and coordinated software (including tracking software) for the ATLAS experiment from 2000 and 2012, co-organized HiggsML challenge in 2014, currently co-coordinator of the ATLAS Machine Learning group.

Sabrina Amrouche, PhD student at University of Geneva, data scientist in pervasive computing, currently working on data evaluation and reference solutions involving machine learning models for track reconstruction.

Laurent Basara, post-doc at LRI-Orsay is tasked with the post-challenge submitted software analysis.

Paolo Calafiura, Computer Scientist at Lawrence Berkeley National Lab, US ATLAS Computing and Software Manager, Principal Investigator of the HEP.TrkX project that investigates novel algorithmic paradigms for particle tracking at the High Luminosity LHC.

Victor Estrade, PhD student at University Paris-Sud; he is currently working on transfer learning methods to reduce systematic uncertainties in HEP analyses..

Steven Farrell, postdoctoral fellow in physics at Lawrence Berkeley National Lab and software developer for ATLAS simulation and analysis code, currently developing machine learning solutions for HEP as part of the HEP.TrkX project.

Cécile Germain, professor of Computer Science at University Paris Sud ; co-organized HiggsML challenge in 2014 ; she is working on supervised and unsupervised machine learning applications to modeling and optimizing complex systems.

Vladimir Vava Gligorov, scientist at LPNHE-Paris, the deputy physics coordinator of the LHCb experiment and formerly in charge of its real-time data processing. He proposed and coauthored the first BDT to be used for real-time data processing in LHCb, and subsequently coordinated the introduction of machine learning techniques throughout the real-time reconstruction and analysis of LHCb data.

Tobias Golling, physicist, associate professor at University of Geneva, experienced with tracking in ATLAS since 2005 and developing machine learning techniques in particle physics.

Heather Gray, physicist, scientist Lawrence Berkeley National Laboratory, detailed studies and responsibilities in ATLAS tracking, improved the performance of ATLAS clustering algorithms in dense environments by introducing a neural-network based algorithm. Exploits machine learning techniques in Higgs analyses.

Isabelle Guyon, professor of informatics at UPSud Paris-Saclay and machine learning researcher. She has extensive experience with organizing machine learning challenges.

Mikhail Hushchyn, PhD student at Moscow Institute of Physics and Technology, data scientist at Yandex-CERN research group. Currently working on track pattern recognition for the SHiP experiment at CERN.

Vincenzo Innocente, Principal Software Scientist at CERN. Responsible for simulation and reconstruction software in three generations of collider experiments at CERN. Currently leader of the Tracking Physics Group in the CMS experiment at the LHC. In machine learning since 1990.

Moritz Kiehn, post-doc at University of Geneva, ACTS developer, also involved in the Silicon hardware R&D

Edward Moyse, Senior Research Scientist at University of Massachusetts Amherst and ATLAS software coordinator. Formerly ATLAS reconstruction convener and one of the lead developers of VP1, an application for event and geometry visualisation.

Andreas Salzburger, physicist at CERN, ACTS project coordinator, co-leader of the design team of the ATLAS Inner Tracker for the high luminosity LHC upgrade, former ATLAS tracking software group convener and reconstruction software group convener.

Andrey Ustyuzhanin, head of Yandex-CERN research group focused on applying Machine Learning to solving Physics problems, organizer of ”Flavour of Physics” challenge on Kaggle, head of laboratory at Higher School of Economics, Russia.

Jean-Roch Vlimant, Associate physicist at the California Institute of Technology. Former CMS tracking software coordinator and reconstruction project coordinator. Advisor and organizer of several HEP-ML events. Principal investigator of several super-computing allocations for deep learning projects. Member of the HEP.TrkX project that investigates novel algorithmic paradigms for particle tracking at the High Luminosity LHC.

Yetkin Yilmaz, physicist, post-doc research assistant in the Applied Statistics and Machine Learning Group of LAL. Developed the code for the TrackMLRamp hackathon at CTD/WIT 2017 workshop in Orsay.