Name: PyHEP 2022 (virtual) Workshop
Start: 2022-09-12T14:00:00+02:00
End: 2022-09-16T23:00:00+02:00
Location: No location set

PyHEP 2022 (virtual) Workshop

from Monday 12 September 2022 (14:00) to Friday 16 September 2022 (23:00)

Monday 12 September 2022
14:00
14:00 - 18:20
Contributions

14:00 Welcome and workshop overview - Eduardo Rodrigues (University of Liverpool (GB))

14:10 Level Up Your Python - Henry Fredrick Schreiner (Princeton University)

15:10 TheBureaucrat, a package to help you organize your work - Matias Senger (University of Zurich (CH))

15:20 Histograms as Objects: Tools for Efficient Analysis and Interactivity - Aman Goel (University of Delhi) Jay Gohil (IRIS HEP Fellow)

15:50 PyHEP and the Climate Crisis [Cancelled] - Hannah Wakeling (McGill University)

16:30 Uproot, Awkward Array, hist, Vector: from basics to combinatorics - Jim Pivarski (Princeton University)

17:00 Python in the Belle II experiment - Yo Sato (KEK IPNS)

17:30 Teaching Python the Sustainable Way: Lessons Learned at HSF Training - Alexander Moreno Briceño (Universidad Antonio Nariño) Aman Goel (University of Delhi) Guillermo Antonio Fidalgo Rodriguez (University of Puerto Rico at Mayagüez)

18:00 Uhepp: Sharing plots in a self-contained format - Frank Sauerburger (Albert Ludwigs Universitaet Freiburg (DE))

18:10 jacobi: Error propagation made easy - Hans Peter Dembinski (TU Dortmund)
Tuesday 13 September 2022
14:00
14:00 - 18:00
Contributions

14:00 iminuit: fitting models to data - Hans Peter Dembinski (TU Dortmund)

15:00 Skyhook: Managing Columnar Data Within Storage - Jayjeet Chakraborty

15:10 The Particle & DecayLanguage packages - Eduardo Rodrigues (University of Liverpool (GB))

15:20 PhaseSpace + DecayLanguage - Simon Thor (CERN)

15:30 Constructing HEP vectors and analyzing HEP data using Vector - Saransh Chopra (Cluster Innovation Centre, University of Delhi)

16:30 Matplotlib with HSF Training - Alexander Moreno Briceño (Universidad Antonio Nariño)

17:30 Lessons learned converting a production-grade Python CMS analysis to distributed RDataFrame - Tommaso Tedeschi (Universita e INFN, Perugia (IT)) Vincenzo Eduardo Padulano (Valencia Polytechnic University (ES))
18:00

18:00 - 18:30
Wednesday 14 September 2022
14:00
14:00 - 18:50
Contributions

14:00 The SuperNova Early Warning System & Software for Studying Supernova Neutrinos - Jost Migenda (King’s College London)

14:30 Python Usage Within the LHCb Experiment - Nathan Grieser (University of Cincinnati (US))

15:00 Basic Physics Analyses Implemented Using Apache Spark. - Luca Canali (CERN)

15:30 Automatic Resource Management with Coffea and Work Queue for analysis workflows - Benjamin Tovar Lopez (University of Notre Dame)

16:30 Data Management Package for the novel data delivery system, ServiceX, and its application to an ATLAS Run-2 Physics Analysis Workflow - Kyungeon Choi (University of Texas at Austin (US))

17:00 EOS -- A software for Flavor Physics Phenomenology - Danny van Dyk

17:30 Correctionlib - Nick Smith (Fermi National Accelerator Lab. (US))

18:00 pyhepmc: a Pythonic interface to HepMC3 - Hans Peter Dembinski (TU Dortmund)

18:10 What's new in Python 3.11 - Henry Fredrick Schreiner (Princeton University)
Thursday 15 September 2022

10:30

10:30 - 11:00
14:00
14:00 - 18:10
Contributions

14:00 Analysis Optimisation with Differentiable Programming - Nathan Daniel Simpson (Lund University (SE))

15:00 Speeding up differentiable programming with a Computer Algebra System - Remco de Boer (Ruhr University Bochum)

15:30 The pythia8 python interface - Michael Kent Wilkinson (University of Cincinnati (US))

16:30 End-to-end physics analysis with Open Data: the Analysis Grand Challenge - Alexander Held (University of Wisconsin Madison (US))

17:30 Awkward RDataFrame Tutorial - Ianna Osborne (Princeton University)

18:00 Developing implicitly-parallel Python analysis tools for NOvA - Derek Doyle (Colorado State University)
18:30 Hackashop
Hackashop
18:30 - 20:30
Contributions

18:30 Intro talk - how to get your set-up to "hack around" - Aman Goel (University of Delhi)
Friday 16 September 2022

10:00

10:00 - 12:00
14:00
14:00 - 18:30
Contributions

14:00 Dask Tutorial - Doug Davis

15:00 Uproot + Dask - Kush Kothari

15:10 Enabling Dask Interoperability with XRootD Storage Systems - Scott Demarest (Florida Institute of Technology)

15:20 3D and VR Industrial Use Cases in Python - Francois Gutherz

15:30 Using C++ From Numba, Fast and Automatic - Baidyanath Kundu (Princeton University (US))

16:30 zfit - binned fits and histograms - Jonas Eschle (University of Zurich (CH))

17:00 abcd_pyhf: Likelihood-based ABCD method for background estimation and hypothesis testing with pyhf - Mason Proffitt (University of Washington (US))

17:30 Pyhf to Combine Converter - Petey Ridolfi

17:40 Scalable, Sparse IO with larcv - Corey Adams

17:50 JetNet library for machine learning in high energy physics - Raghav Kansal (Univ. of California San Diego (US))

18:00 Workshop close-out - Eduardo Rodrigues (University of Liverpool (GB))

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