PyHEP 2025 - "Python in HEP" Users Workshop (hybrid), CERN

Speaker List

• Mohamed Aly (Princeton University (US))
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    Smart Gradient-Based Optimization of HEP Analyses

• Viren Bhanot (CERN)
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    Simulations, Post-Processing and Visualisations of Detector Cooling Systems

• Giuseppe De Laurentis (University of Edinburgh)
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    Scattering Amplitude Reconstruction in Python

• Manfred Peter Fackeldey (Princeton University (US))
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    evermore: differentiable binned likelihoods in JAX

• Matthew Feickert (University of Wisconsin Madison (US))
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    Reproducible reuse by default: Use of Pixi for software in (Py)HEP

• Benjamin Fischer (RWTH Aachen University (DE))
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    Workflows via ParaO - Parametrizing Objects

• Martin Foll (University of Oslo (NO))
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    Zero-overhead ML training from Python with ROOT in an ATLAS Open Data analysis

• Jan Gavranovic (Jozef Stefan Institute (SI))
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    From ROOT to PyTorch: Seamless Data Pipelines with HDF5

• Lino Oscar Gerlach (Princeton University (US))
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    Smart Gradient-Based Optimization of HEP Analyses

• Cameron Harris
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    FLARE: FCCee b2Luigi Automated Reconstruction And Event processing

• Aditi Juneja
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    Accelerating scientific Python code with dispatching: Graphs and Arrays

• Iason Krommydas (Rice University (US))
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    Coffea schemas modifications

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    Coffea Framework: Current Status and Recent Updates

• Mingrun Li
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    uproot-custom: customize branch data reading in Uproot

• Thomas McCauley (University of Notre Dame (US))
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    ISpy NanoAOD: An event display for the NanoAOD format of the CMS Experiment

• Maksym Naumchyk
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    Coffea schemas modifications

• Alexander Puck Neuwirth (UNIMIB & INFN)
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    PyLHE in 2025: New features and improvements

• Ianna Osborne (Princeton University)
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    Welcome and workshop overview

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    Workshop close-out

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    Awkward Array Internals: A Hands-On Hacking Session

• Andres Rios-Tascon (Princeton University)
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    Reviving Formulate

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    RNTuple and Uproot

• Henry Fredrick Schreiner (Princeton University)
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    Histogram Serialization

• Nick Smith (Fermi National Accelerator Lab. (US))
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    PyTrees for vectors

• Ashwin Srinath
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    Pythonic GPU Parallelism for HEP with cuda-cccl

• Giordon Holtsberg Stark (University of California,Santa Cruz (US))
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    (Super)powering ntuple analysis with coffea for ATLAS

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    Efficient Statistical Modeling for Particle Physics Using Computational Graphs in Python

• Silia Taider (CERN)
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    ROOT's Newest Pythonizations: UHI, RDataFrame and More

• Benjamin Tovar Lopez (University of Notre Dame)
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    Wrangling Massive Task Graphs with Dynamic Hierarchical Composition

• Liv Helen Vage (Princeton University (US))
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    Up your ML game: an overview of Python ML tools relevant to HEP

• David Walter (Massachusetts Inst. of Technology (US))
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    Efficient binned profile likelihood maximization with Rabbit

• Felix Philipp Zinn (Rheinisch Westfaelische Tech. Hoch. (DE))
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    evermore: differentiable binned likelihoods in JAX

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    PocketCoffea: Configuration Framework for CMS Analyses based on Coffea