ACAT 2019

Speaker List

• Nicola Louise Abraham (University of Sussex (GB))
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    The design and performance of the ATLAS Inner Detector trigger in high pile-up collisions at 13 TeV at the Large Hadron Collider

• Sadaf Roohi Alam (ETHZ - ETH Zurich)
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    Making HPC friendly for scientists

• Thomas Alef (University of Bonn (DE))
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    Incorporation of Systematic Uncertainties in the Training of Multivariate Methods

• Andrey Arbuzov (Joint Institute for Nuclear Research (RU))
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    QED and electroweak radiative corrections to polarized Bhabha scattering

• Giuseppe Avolio (CERN)
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    The Central Hint and Information Processor system for automation, error detection and recovery in the ATLAS TDAQ Controls framework

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    Multi-threaded checksum computation for the ATLAS high-performance storage software

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    Performance evaluation of distributed file systems for the phase-II upgrade of the ATLAS experiment at CERN

• Jan Balewski
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    STAR Data Production Workflow on HPC: Lessons Learned & Best Practices

• Vladislav Belavin (CERN)
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    Electromagnetic-shower generation with Graphical GANs

• Alexander Belyaev (University of Southampton & Rutherford Appleton Laboratory)
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    Decoding the nature of Dark Matter at current and future experiments

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    Decoding the nature of Dark matter at current and future experiments

• Nectarios Benekos (University of Peloponnese (GR))
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    Overall quality optimization for DQM stage in High Energy Physics experiments

• Iliana Betsou (National Technical Univ. of Athens (GR))
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    New ROOT graphics language

• Wahid Bhimji (Lawrence Berkeley National Lab. (US))
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    Deep Learning on HPC at NERSC

• Rafal Bielski (CERN)
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    ATLAS High Level Trigger within the multi-threaded software framework AthenaMT

• Serguei Bityukov (Institute for High Energy Physics (RU))
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    Method for results comparison of various versions of simulation program by the use of experimental data

• Tommaso Boccali (INFN Sezione di Pisa, Universita' e Scuola Normale Superiore, P)
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    CMS Software and Offline preparation for future runs

• Andrea Bocci (CERN)
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    Towards a heterogeneous High Level Trigger farm for CMS

• Misha Borodin (University of Iowa (US))
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    The second generation of the ATLAS Production System: expertise and future evolution

• Patrick Bos (Nikhef National institute for subatomic physics (NL))
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    RooFit parallelization efforts

• Petr Bouř (FNSPE CTU Prague)
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    Prong Formation in NOvA Reconstruction Pipeline

• Johan Bregeon
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    DIRAC: Putting together heterogeneous resources for scientific applications

• Johann Brehmer (New York University)
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    Keynote talk: Constraining effective field theories with machine learning

• Rene Brun (CERN)
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    Keynote talk: The future of HEP computing

• Andy Buckley (University of Glasgow (GB))
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    Computational challenges for Generators

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    Global fits of BSM physics models with Gambit

• Michael Bussmann (Helmholtz-Zentrum Dresden - Rossendorf)
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    Computations in Laser Particle Acceleration: heterogenous, parallel computing for physicists

• Anne Cadiou (CNRS)
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    In-situ analysis and visualization of massively parallel computations of transitional and turbulent flows

• Hao Cai (Wuhan University (CN))
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    Introduction to the Full Bandwidth Amplitude Analysis Software (FALLS)

• Paolo Calafiura (Lawrence Berkeley National Lab. (US))
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    Computing Architectures in the HL-LHC era

• Daniel Hugo Campora Perez (Universidad de Sevilla (ES))
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    Core software challenges of the GPU High Level Trigger 1 of LHCb

• Gevy Cao (Queen's University)
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    Particle Identification In PICO Using Semi-supervised Learning

• Federico Carminati (CERN)
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    Thank you and good bye

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    Welcome to ACAT 2019 in Saas Fee!

• Stefano Carrazza (CERN)
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    Riemann-Theta Boltzmann Machine

• Marco Cattaneo (CERN)
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    The computing model of the LHCb Upgrade

• Riccardo Cenci (Universita & INFN Pisa (IT))
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    Real-time reconstruction of long-lived particles at LHCb using FPGAs.

• Olmo Cerri (California Institute of Technology (US))
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    Pileup mitigation with graph neural networks

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    Tagging Higgs bosons at the LHC with Interaction Networks

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    Variational Autoencoders for New Physics Mining at the Large Hadron Collider

• Oscar Roberto Chaparro Amaro
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    Vectorization techniques for probability distribution function using VecCore

• Zhenjing Cheng (INSTITUE OF HIGH ENERGY PHYSICS)
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    Automated and Intelligent Data Migration Strategy in High Energy Physical Storage Systems

• Isabelle Cherney (Merrimack University)
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    The STEM paradox: Factors affecting diversity in STEM fields

• Soumith Chintala (Facebook AI Research)
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    Automatic Differentiation and Deep Learning

• Collaboration CMS
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    CMS Software and Offline preparation for future runs

• Alina Corso Radu (University of California Irvine (US))
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    Controls and Configuration software for the ATLAS DAQ system in LHC Run 2

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    ELisA: the ATLAS logbook facility extensions

• Ben Couturier (CERN)
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    DIRACOS: a cross platform solution for grid tools

• Joshua Davies (Karlsruhe Institute of Technology)
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    Double Higgs boson production in the high- and low-energy limits

• Pablo de Castro (Universita e INFN, Padova (IT))
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    INFERNO: Inference-Aware Neural Optimisation

• Elise de Doncker (Western Michigan University)
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    Numerical multi-loop integration on heterogeneous many-core processors

• ziyan deng (Institute of High Energy Physics, Beijing)
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    TAG based data analysis in BESIII offline sofware

• Andrea Di Luca (Universita degli Studi di Trento and INFN (IT))
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    Real-time reconstruction of long-lived particles at LHCb using FPGAs.

• Laura Domine (Stanford University/SLAC)
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    Submanifold Sparse Convolutional Networks for Sparse, Locally Dense Particle Image Analysis

• Philipp Do Nascimento Gaspar (Federal University of of Rio de Janeiro (BR))
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    Towards the Increase in Granularity for the Main Hadronic ATLAS Calorimeter: Exploiting Deep Learning Methods

• Frederic Alexandre Dreyer (Oxford)
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    Reinforced Jet Grooming

• Victor Estrade (LRI)
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    Uncertainty reduction by gradient descent

• Riccardo Farinelli (Universita e INFN, Ferrara (IT))
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    A fast and parametric digitization for triple-GEM detectors

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    GRAAL: Gem Reconstruction And Analysis Library

• Torben Ferber (University Of British Columbia)
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    Electromagnetic calorimeter reconstruction in Belle II

• Benjamin Fischer (Rheinisch-Westfaelische Tech. Hoch. (DE))
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    Adversarial Neural Network-based data-simulation corrections for jet-tagging at CMS

• Conor Fitzpatrick (Ecole Polytechnique Federale de Lausanne (CH))
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    A 30 MHz software trigger and reconstruction for the LHCb upgrade

• Alessandra Forti (University of Manchester (GB))
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    Hardware Accelerated ATLAS Workloads on the WLCG

• Simone Francescato (Sapienza Universita e INFN, Roma I (IT))
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    Fast Deep Learning on FPGAs for the Phase-II L0 Muon Barrel Trigger of the ATLAS Experiment

• Markus Frank (CERN)
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    DD4hep: an integrated detector description tool for HEP

• Frank-Dieter Gaede (Deutsches Elektronen-Synchrotron (DE))
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    DD4hep: an integrated detector description tool for HEP

• Yongsheng Gao (California State University (US))
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    Explore cloud solutions for ATLAS with $250,000 AWS cloud credits

• Luis Miguel Garcia Martin (Univ. of Valencia and CSIC (ES))
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    Best Track 2 poster: Tracking performance for long living particles at LHCb

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    Tracking performance for long living particles at LHCb

• Andrei Gheata (CERN)
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    Performance results of the GeantV prototype with complete EM physics

• Aishik Ghosh (Centre National de la Recherche Scientifique (FR))
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    Deep generative models for fast shower simulation in ATLAS

• Domenico Giordano (CERN)
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    Next Generation of HEP CPU Benchmarks

• Jonas Glombitza (RWTH Aachen)
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    Deep Learning based Algorithms in Astroparticle Physics

• Artem Golovatiuk (University of Naples (IT))
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    Deep learning for Directional Dark Matter search

• Dayane Gonçalves (Universidade Federal de Juiz de Fora)
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    Energy reconstruction of the ATLAS Tile Calorimeter under high pile-up conditions using the Wiener filter

• Heather Gray (LBNL)
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    HEP.QPR Project: Quantum Pattern Recognition for Charged Particle Tracking

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    The HEP.QPR Project: Quantum Pattern Recognition for Charged Particle Tracking

• Maria Grigoryeva (Institute for Theoretical and Experimental Physics (RU))
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    A New Visual Analytics toolkit for ATLAS metadata

• Wen Guan (University of Wisconsin (US))
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    Application on LHC High Energy Physic data analysis with IBM Quantum Computing

• Jean-Philippe Guillet (LAPTh CNRS)
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    Toward an efficient evaluation of two-loop massive scalar integralss

• Atilim Gunes Baydin (University of Oxford)
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    Keynote talk: Probabilistic Programming and Inference in Particle Physics

• Hong Guo (Institute of Applied Physics and Computational Mathematics)
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    Parallel computing of Overlapping Grids Applications based on A Patch-based Communication Algorithm

• Frank K. Gürkaynak (ETH)
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    RISC-V based, silicon proven open-source processors from the PULP project

• Christophe Haen (CERN)
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    DIRACOS: a cross platform solution for grid tools

• Stephan Hageboeck
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    A more Pythonic, Interoperable and Modern PyROOT

• Stephan Hageboeck (University of Bonn (DE))
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    Making RooFit Ready for Run 3

• Alexander Hagen (Pacific Northwest National Laboratory)
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    Scaling the training of semantic segmentation on MicroBooNE events to multiple GPUs

• Thomas Hahn (MPI f. Physik)
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    New Features in FeynArts & Friends, and how they got used in FeynHiggs

• Benedikt Hegner (CERN)
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    Distributed Computing Services in Belle II

• Christoph Heidecker (KIT - Karlsruhe Institute of Technology (DE))
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    Boosting Performance of Data-intensive Analysis Workflows with Distributed Coordinated Caching

• Lukas Alexander Heinrich (New York University (US))
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    Continuous Analysis in ATLAS: Running User-Defined Container Images on the Grid

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    Excursion Set Estimation using Sequential Entropy Reduction for Efficient Searches for New Physics at the LHC

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    pyhf: auto-differentiable binned statistical models

• Valentin Jonathan Hirschi (SLAC)
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    Machine Learning helping Monte-Carlo collider simulations

• Stephen Philip Jones
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    GPU usage in theoretical calculations

• Soon Yung Jun (Fermi National Accelerator Lab. (US))
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    Geant4 Parameter Tuning Using Professor

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    Vectorization of random number generation and reproducibility of concurrent particle transport simulation

• James Kahn (Karlsruhe Institute of Technology (KIT))
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    Selective background Monte Carlo simulation at Belle II

• Oleg Kalashev (Institute for Nuclear Research RAS)
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    Using Deep Learning in Ultra-High Energy Cosmic Ray Experiments

• Andrei Kataev (Institute for Nuclear Research of the Academy of Sciences of Russia)
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    Forgotten (or not) possibility of the application of the least squares method: the analysis of the computer-based numerical results to QCD $\rm{\overline{MS}}$-on-shell mass relation at the four-loop level

• Andrei Kazarov (Petersburg Nuclear Physics Institut (RU))
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    Controls and Configuration software for the ATLAS DAQ system in LHC Run 2

• Nikita Kazeev (Yandex School of Data Analysis (RU))
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    Machine Learning for Muon Identification at LHCb

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    Machine Learning on sWeighted data

• Doris Yangsoo Kim (Soongsil University)
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    The Belle II Simulation Library

• Fabian Klimpel (Max-Planck-Institut fur Physik (DE))
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    Track propagation for different detector and magnetic field setups in Acts

• Igor Kondrashuk (UBB)
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    Algorithm to find an all-order in the running coupling solution to an equation of the DGLAP type

• Alexandr Korobov (NSU)
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    Data-driven Monte Carlo Generator for Low Energy e+e- Annihilation to Hadrons

• Dirk Krucker (Deutsches Elektronen-Synchrotron (DE))
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    Direct optimisation of the discovery significance when training neural networks to search for new physics in particle colliders

• Yoshimasa Kurihara (KEK)
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    Recent developments of GRACE system

• David Lange (Princeton University (US))
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    An analytics driven computing model for HL-LHC

• Francois Lanusse (Lawrence Berkeley National Laboratory )
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    Machine learning in cosmology

• Stefano Laporta (Dipartimento di Fisica, Universita di Bologna)
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    Techniques for the calculation of 4-loop QED contributions

• David Lawrence (Jefferson Lab)
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    Multi-threaded Event Reconstruction with JANA

• Federico Lazzari (Universita & INFN Pisa (IT))
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    Real-time cluster finding for LHCb silicon pixel VELO detector using FPGA

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    Real-time reconstruction of long-lived particles at LHCb using FPGAs.

• Charles Leggett (Lawrence Berkeley National Lab (US))
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    Simulating Diverse HEP Workflows on Heterogeneous Architectures

• Li Liao
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    A Domain Specific IDE for Parallel Application Development

• Etienne Lyard (University of Geneva)
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    Probing Neural Networks for the Gamma/Hadron Separation of CTA

• Artem Maevskiy (National Research University Higher School of Economics (RU))
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    Fast Data-Driven simulation of Cherenkov Detectors Using Generative Adversarial Networks.

• Daniel Maitre
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    Ntuples for NNLO processes

• Oliver Majersky (Comenius University (SK))
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    Identifying hadronically decaying vector bosons and top quarks in ATLAS

• Konstantin Malanchev
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    Fips: An OpenGL based FITS viewer

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    Machine Learning Study of Open Supernova Catalog

• Mario Masciovecchio (Univ. of California San Diego (US))
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    Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures with the CMS Detector

• Andrea Massironi (CERN)
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    Heterogenous computing for the local reconstruction algorithms of the CMS calorimeters

• Patricia Mendez Lorenzo (CERN)
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    Track 1 summary

• Lorenzo Moneta (CERN)
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    ROOT Based Analysis: From Data to Plots, Expressive, Easy and Fast

• Michael J. Morello (SNS and INFN-Pisa (IT))
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    Real-time reconstruction of long-lived particles at LHCb using FPGAs.

• Simone Mosciatti (Politecnico di Milano (IT))
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    CernVM-FS Container Image Integration

• Katharina Mueller (Universitaet Zuerich (CH))
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    Machine Learning approach to boosting neutral particles identification in the LHCb calorimeter

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    Machine Learning for Muon Identification at LHCb

• Axel Naumann (CERN)
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    The Practitioner’s C++17 and 20 News

• Jennifer Ngadiuba (CERN)
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    FPGA-accelerated machine learning inference as a solution for particle physics computing challenges

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    hls4ml: deploying deep learning on FPGAs for trigger and data acquisition

• Thong Nguyen (California Institute of Technology (US))
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    Recurrent GANs for particle-based simulation at the LHC

• Minh Duc Nguyen (Lomonosov Moscow State University Skobeltsyn Institute of Nuclear Physics)
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    Applying data access policy to CernVM-FS

• Makiko Nio (RIKEN)
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    Higher-order QED contributions to the lepton anomalous magnetic moments

• Dennis Noll (Rheinisch Westfaelische Tech. Hoch. (DE))
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    Reinforced Sorting Networks for Particle Physics Analyses

• Niklas Nolte (CERN / Technische Universitaet Dortmund (DE))
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    The core software framework for the LHCb Upgrade

• Noel Aaron Nottbeck (Johannes Gutenberg Universitaet Mainz (DE))
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    Highly performant, Deep Neural Networks with sub-microsecond latency on FPGAs for trigger applications

• Alexander Nozik (INR RAS / MIPT)
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    DataForge: declarative approach to scientific data processing automation

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    Kotlin - new language for scientific programming

• Sydney Otten (Radboud Universiteit Nijmegen)
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    DeepXS: Fast approximation of MSSM electroweak cross sections at NLO

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    PhenoAI and iDarkSurvey: Learning (from) high-dimensional models

• Marco Peruzzi (CERN)
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    The NanoAOD event data format in CMS

• Marko Petric (CERN)
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    ConformalTracking: a geometry agnostic tracking library

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    DD4hep: an integrated detector description tool for HEP

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    DIRACOS: a cross platform solution for grid tools

• Leo Piilonen (Virginia Tech)
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    Belle2VR – An Interactive Virtual Reality Visualization of GEANT4 Event Histories

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    Track extrapolation and muon identification with GEANT4E in Belle II event reconstruction

• Jim Pivarski (Princeton University)
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    Nested data structures in array and SIMD frameworks

• Michael Poat (Brookhaven National Laboratory)
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    STAR Data Production Workflow on HPC: Lessons Learned & Best Practices

• Adrian Alan Pol (Université Paris-Saclay (FR))
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    Deep learning for certification of the quality of the data acquired by the CMS experiment

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    Monitoring of time evolution of the trigger rates exploiting deep representation learning at the CMS experiment

• Jefferson Porter
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    STAR Data Production Workflow on HPC: Lessons Learned & Best Practices

• Stanislav Poslavskii (Institute for High Energy Physics of NRC Kurchatov Institute (R)
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    Computer algebra in physics research: algorithms, systems and modern developments

• Stanislav Poslavsky (IHEP, Protvino)
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    Rings: an efficient library for polynomial rings

• Alexandre Poukhov
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    micrOMEGAs5.0

• Michelangelo Preti (Ecole Normale Supérieure - CNRS)
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    STR: a Mathematica package for the method of uniqueness

• steven prohira (The Ohio State University)
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    Weak signal extraction using matrix decomposition

• Konstantin Pugachev (Budker Institute of Nuclear Physics (RU))
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    The DQM system for the SND

• Giovanni Punzi (Universita & INFN Pisa (IT))
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    Real-time reconstruction of long-lived particles at LHCb using FPGAs.

• Narayan Rana (INFN Milan)
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    Three loop QCD corrections to heavy quark form factors

• Rajesh Ranganath (New York University)
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    Implicit cause models

• Yannik Alexander Rath (RWTH Aachen University (DE))
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    Physics inspired feature engineering with Lorentz Boost Networks

• daniel ratner (Stanford University)
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    Machine learning for an X-ray FEL

• Essma Redouane Salah (University of M'sila Algeria)
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    Phase Space Integration of initial state radiation in p-p interaction

• Danilo Rezende (DeepMind)
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    Generative Models

• Pier Paolo Ricci (INFN CNAF)
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    An innovative monitoring and maintenance model for the INFN CNAF Tier-1 data center infrastructure.

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    CDF Long Term Data Preservation at the INFN CNAF Tier-1 data center: the Oracle database and software framework replica.

• Marcel Rieger (Rheinisch-Westfaelische Tech. Hoch. (DE))
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    Design Pattern for Analysis Automation on Interchangeable, Distributed Resources using Luigi Analysis Workflows

• Martin Ritter
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    Selective background Monte Carlo simulation at Belle II

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    Jupyter Notebook Support of the Belle 2 Software

• Gareth Douglas Roy (University of Glasgow (GB))
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    Using Continuous Deployment techniques to manage software change at a WLCG Tier-2

• Ben Ruijl (Nikhef)
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    reFORM: designing a new symbolic manipulation toolkit

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    Track 3 Summary

• Artem Ryzhikov (Yandex School of Data Analysis (RU))
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    Variational Dropout Sparsification for Particle Identification speed-up.

• Renat Sadykov (Joint Institute for Nuclear Research (RU))
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    MCSANCee generator with one-loop electroweak corrections for processes with polarized e^+e^- beams

• Andre Sailer (CERN)
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    DD4hep: an integrated detector description tool for HEP

• Matthias Jochen Schnepf (KIT - Karlsruhe Institute of Technology (DE))
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    HEP Analyses on Dynamically Allocated Opportunistic Computing Resources

• York Schröder (UBB Chillán)
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    Renormalization of gauge theories at five loops

• Felix Schuermann (EPFL)
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    Neuroscience and the Future of Computing

• Ludovic Michel Scyboz (Max-Planck-Institut fur Physik (DE))
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    Trilinear Higgs boson coupling variations for di-Higgs production with full NLO QCD predictions in POWHEG

• Oksana Shadura (National Academy of Sciences of Ukraine (UA))
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    Evolution of ROOT package management

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    ROOT I/O compression algorithms and their performance impact within Run 3

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    Speeding HEP Analysis with ROOT Bulk I/O

• Sergey Shirobokov (Yandex School of Data Analysis (RU))
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    Accelerating dark matter search in emulsion SHiP detector by Deep Learning

• Antoni Shtipliyski (Imperial College (GB))
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    Primary Vertex Reconstruction with Deep Learning in FPGAs for the Phase-2 Upgrade of the Level-1 Trigger of CMS

• Sebastian Skambraks (Technische Universität München)
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    A 3D Track Finder for the Belle II CDC L1 Trigger

• Andreas Sogaard (University of Edinburgh (GB))
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    Constructing mass-decorrelated hadonic decay taggers in ATLAS

• Michael David Sokoloff (University of Cincinnati (US))
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    A hybrid deep learning approach to vertexing

• Carlos Solans Sanchez (CERN)
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    The “FELIX” detector interface for the ATLAS Trigger and Data Acquisition upgrades and its deployment in the ATLAS Inner Tracker demonstrator setup

• Werner Spolidoro Freund (Federal University of of Rio de Janeiro (BR))
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    An Ensemble of Neural Networks for Online Electron Filtering at the ATLAS Experiment.

• Matej Srebre (LMU Munich)
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    Pixel detector background simulation using generative adversarial networks at Belle II

• Mantas Stankevicius (Fermi National Accelerator Lab. (US))
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    Meta-Learning for Artificial Neural Network Hyper-Parameter Optimization for CERN CMS Offline Data Certification

• Constantin Steppa (University of Potsdam)
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    Air shower reconstruction with hexagonal convolutional neural networks

• William Lawrence Sutcliffe (Karlsruhe Institute of Technology (DE))
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    Full Event Intepretation at Belle II

• Yavar Taheri Yeganeh (Shahid Beheshti University)
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    Exploring Hybrid Deep Learning Architecture for Experimental HEP Data Analysis

• Yuka Takahashi (Princeton University (US))
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    Migrating large codebases to C++ Modules

• Kazuhiro Terao (SLAC)
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    Machine Learning in Neutrino Physics

• Victoria Tokareva (Karlsruhe Institute of Technology (KIT))
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    Setting up technical requirements for an astroparticle data life cycle

• Mirco Tracolli (INFN Perugia)
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    Using DODAS as deployment manager for smart caching of CMS data management system

• Jakub Trusina (Czech Technical University (CZ))
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    Generalization of Homogeneity Tests Used in High Energy Physics Experiments

• Ilkay Turk Cakir (Istanbul Aydin University)
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    A virtualized Tier-3g Facility Installiation in WLCG Network of CERN

• Takahiro Ueda (KEK)
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    Further developments of FORM

• Gokhan Unel (University of California Irvine (US))
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    CutLang: a cut based HEP analysis description language and interpreter

• Alexander Kryukov UNKNOWN (MSU)
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    Computer algebra algorithm of simplification of tensor polynomials

• Andrey Ustyuzhanin (Yandex School of Data Analysis (RU))
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    Track 2 Summary

• Sofia Vallecorsa (Gangneung-Wonju National University (KR))
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    Generative Adversarial Networks for fast simulation: generalisation and distributed training in HPC

• Matei Vasile (IFIN-HH (RO))
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    Evaluating InfluxDB and ClickHouse database technologies for improvements of the ATLAS operational monitoring data archiving

• Andrii Verbytskyi (Max-Planck-Institut fur Physik (DE))
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    HepMC3 Event Record Library for Monte Carlo Event Generators

• Miguel Villaplana (Università degli Studi e INFN Milano (IT))
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    The ATLAS EventIndex and its evolution towards LHC Run 3

• Jean-Roch Vlimant (California Institute of Technology (US))
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    Charged Particle Tracking as a QUBO problem solved with Quantum Annealing-Inspired Optimization

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    HEP.TrkX Charged Particle Tracking using Graph Neural Networks

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    TrackML : a tracking Machine Learning challenge

• Sergey Volkov
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    Numerical calculation of high-order QED contributions to the electron anomalous magnetic moment

• Dorothea Vom Bruch (LPNHE Paris, CNRS)
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    Best Track 1 poster: Physics and computing performance of reconstruction algorithms for the GPU High Level Trigger 1 of LHCb

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    Physics and computing performance of reconstruction algorithms for the GPU High Level Trigger 1 of LHCb

• Ralf Florian Von Cube (Rheinisch-Westfaelische Tech. Hoch. (DE))
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    Federation of compute resources available to the German CMS community

• Barthelemy Von Haller (CERN)
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    Data Sampling challenges in the ALICE O2 distributed processing system

• Wolfgang Waltenberger (Austrian Academy of Sciences (AT))
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    Updates on SModelS

• Lu Wang (Computing Center,Institute of High Energy Physics, CAS)
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    Parameter tuning of distributed storage system based on reinforcement learning

• Gordon Watts (University of Washington (US))
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    ACAT 2019 Summary

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    Aligning the MATHUSLA test stand detector: Using TensorFlow

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    Beyond the Roadmap: HL-LHC HEP Software

• Zhanchen Wei (IHEP, CAS)
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    In-Memory Parallel Computing for Partial Wave Analysis

• Monique Werlen (EPFL - Ecole Polytechnique Federale Lausanne (CH))
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    Denis Perret-Gallix (1949-2018)

• Linghui Wu
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    Digitization of Cylindrical GEM Detector

• Oskar Wyszynski (CERN)
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    Machine Learning Techniques in the ATLAS TDAQ Network Monitoring System

• Qi Xu (Institute of High Energy Physics,Chinese Academy of Sciences)
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    Cross-domain Data Access System for Distributed Sites in HEP

• Yuan Ye (Institue of High Energy Physics, China)
  • Speaker at

    Deep Learning applied to hit classification for BESIII drift chamber

  • Speaker at

    Production experience and performance study for HEP data production at HPC-TianheII

• Andrey Zarochentsev (St Petersburg State University (RU))
  • Speaker at

    Federated data storage evolution in HENP: data lakes and beyond

  • Speaker at

    JupyterLab at the Saint Petersburg State University

• Yao Zhang
  • Speaker at

    Deep Learning applied to hit classification for BESIII drift chamber

  • Speaker at

    Production experience and performance study for HEP data production at HPC-TianheII

• Yana Zhezher (INR RAS & Lomonosov MSU)
  • Speaker at

    Boosted decision trees in the classification tasks with the Telescope Array surface detector data