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    ZPW2026: Machine Learning Techniques for Particle Physics

    → Europe/Zurich
    KOL-G-217 (UZH Main Building)

    KOL-G-217

    UZH Main Building

    Raemistrasse 71, 8006 Zurich
    Description

    The Zurich Phenomenology Workshop has been organized for the first time by ETH and the University of Zurich in 2009. Over the years, the Workshop has developed into a forum for particle physics researchers to discuss the latest developments in phenomenology. 

    In 2026 we will have a focus on rapidly evolving role of machine learning in high energy physics. We will cover a range of topics from phenomenology to detector design. The ZPW 2026 will provide a forum to discuss emerging opportunities where machine learning can advance precision calculation, beyond the Standard Model physics and discovery potential across the field.

    The workshop, organized jointly by the particle theory groups of UZH and ETH with the support of the Pauli Center for Theoretical Studies, will be held on January 5-7, 2026.

     

    Registration is now closed. 

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    Participants
    121 View full list
    • Monday 5 January
      • 1
        Registration KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • 2
        Welcome KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 1: Deep learning and neutrino physics KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Florencia Canelli (University of Zurich (CH))
        • 3
          Experimental View on Deep Learning for Neutrino experiments
          Speaker: Davide Sgalaberna (ETH Zurich (CH))
          ML for neutrinos.pdf
        • 4
          Algorithmic View on Deep Learning for Accelerator Neutrino Experiments
          Speaker: Dr Saul Alonso Monsalve (ETH Zurich)
          zpw-sam-26-01-05.pdf
      • 5
        Coffee break KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 2: Machine Learning and Lattice Field Theory KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Marina Krstic Marinkovic (ETH Zurich)
      • 8
        Lunch KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 3: Optimal transport, anomaly detection KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Nicola Serra (University of Zurich (CH))
        • 9
          Optimal Transport: from A to B...and beyond
          Speaker: Prof. Alessio Figalli (ETH)
          Figalli-2026.pdf
        • 10
          Data to theory: how to fuel BSM model building with anomaly detection
          Speaker: Maurizio Pierini (CERN)
          ZPW2026.pdf
      • 11
        Coffee break KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 4: Machine learning for reconstruction KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Thomas Gehrmann (Univ. Zurich)
    • Tuesday 6 January
      • Session 5: Machine Learning for NNLO QCD and Amplitude Surrogates KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Thomas Gehrmann (Univ. Zurich)
        • 14
          Variance reduction with Normalizing Flows - Application to NNLO QCD phase space integration
          Speaker: Rene Poncelet (IFJ PAN Krakow)
          2026.01.06-Zurich-ZPW-poncelet.pdf
        • 15
          Learning reliable amplitude surrogates
          Speaker: Nina Elmer (University of Cambridge)
          ZPW26_Elmer.pdf
      • 16
        Coffee break KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 6: Perturbative QCD and Matrix Elements KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Gino Isidori (University of Zurich (CH))
      • 19
        Lunch KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 7: Machine Learning for Fundamental Physics and Discovery KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Thea Aarrestad (ETH Zurich (CH))
        • 20
          On Foundation models for Fundamental Science [Title to be confirmed]
          Speaker: Michael Kagan (SLAC National Accelerator Laboratory (US))
          Kagan_ZPW2026.pdf
        • 21
          OmniLearn: A Method to Simultaneously Facilitate All Jet Physics Tasks and beyond
          Speaker: Vinicius Massami Mikuni (Lawrence Berkeley National Lab. (US))
          OmniLearned.pdf
        • 22
          AI for Discovery
          Speaker: Gregor Kasieczka (Hamburg University (DE))
          DeepLearning_ZPW_2026.pdf
      • 23
        Coffee break KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 8: Machine Learning for PDFs, Unfolding and Precision Physics KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Javad Komijani (ETH Zurich)
        • 24
          Uncertainty Quantification in PDF Determinations
          Speaker: Luigi Del Debbio (The University of Edinburgh (GB))
          Zurich26.pdf
        • 25
          Unfolding, Precision, and Machine Learning
          Speaker: Kyle Cormier (CERN)
          Unfolding_Precision_ML_ZPW_2026.pdf
      • 26
        Dinner

        Restaurant Zum Alten Löwen, Universitätstrasse 111, 8006 Zürich.
        Directions: Directions on Google Maps
        Bus line 33 or tram lines no. 9 & 10,
        Rigiblick cable car stop.

    • Wednesday 7 January
      • Session 9: Machine Learining in Cosmology KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Marcelle Soares-Santos (University of Zürich)
        • 27
          Can AI Enable Next Breakthroughs in Large-Scale Structure Cosmology?
          Speaker: Tomasz Kacprzak
          tomaszk_uzh_260107.pdf
        • 28
          Simulation-based inference for gravitational-wave data analysis
          Speaker: Konstantin Leyde
          260107_zurich.pdf
      • 29
        Coffee break KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
      • Session 10: Machine Learning for Detector Design KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich
        Convener: Nicola Serra (University of Zurich (CH))
        • 30
          On Detector Design with Differential Methods
          Speaker: Jan Kieseler (KIT - Karlsruhe Institute of Technology (DE))
          20260107.pdf
        • 31
          On Detector Design with Artificial Intelligence
          Speaker: Shah Rukh Qasim (University of Zurich (CH))
          ZPW26_AI_for_Design.key
      • 32
        Lunch KOL-G-217

        KOL-G-217

        UZH Main Building

        Raemistrasse 71, 8006 Zurich