Name: Neutrino Physics and Machine Learning 2024
Start: 2024-06-25T08:30:00+02:00
End: 2024-06-28T22:15:00+02:00
Location: ETH Zurich

Neutrino Physics and Machine Learning 2024

from Tuesday, June 25, 2024 (8:30 AM) to Friday, June 28, 2024 (10:15 PM)

Monday, June 24, 2024
Tuesday, June 25, 2024

8:30 AM Registration
Registration
8:30 AM - 8:50 AM
Room: HCI J4
8:50 AM
8:50 AM - 12:15 PM
Room: HCI J4
Contributions

8:50 AM Welcome to ETH - Saul Alonso Monsalve (ETH Zurich)

9:05 AM Overview of machine learning applications in JUNO - Teng Li (Shandong University)

9:40 AM Machine-Learning based photon counting for PMT waveforms and its application to the energy reconstruction of JUNO - Guihong Huang (Wuyi University)

10:05 AM Interpretable machine learning approach for electron antineutrino selection in the JUNO experiment - Arsenii Gavrikov (INFN-Padova + The University of Padova)

11:00 AM Reconstruction of atmospheric neutrino’s directionality in JUNO with machine learning - Feng Gao (Université libre de Bruxelles (ULB))

11:25 AM Identification of atmospheric neutrino's flavor in JUNO with machine learning - Wing Yan Ma (Shandong University, China)

11:50 AM Deep learning approaches for fast event reconstruction in the SNO+ scintillator phase and beyond - Cal Hewitt (University of Oxford) Mark Anderson (Queen's University)
12:15 PM Lunch break
Lunch break
12:15 PM - 1:35 PM
1:35 PM
1:35 PM - 5:55 PM
Room: HCI J4
Contributions

1:35 PM Identifying Neutrino Final States in MicroBooNE with a New Deep-Learning Based LArTPC Reconstruction Framework - Matthew Rosenberg (Tufts University)

2:00 PM Using CNN for a Dark Trident Search at MicroBooNE - Luis Mora Lepin

2:25 PM Data-Driven Light Model for the MicroBooNE Experiment - Polina Abratenko (Tufts University)

2:55 PM Particle Trajectory Reconstruction and Euclidian Equivariant Neural Networks - Omar Alterkait (Tufts University / IAIFI)

3:25 PM Deep Learning applications for electron neutrino reconstruction in the ICARUS experiment - Dae Heun Koh (SLAC) Drielsma Francois (SLAC)

4:30 PM Muon Neutrino Reconstruction and Neutral Pion Calibration with Machine Learning Techniques at the ICARUS Detector - Daniel Carber (Colorado State University, Fort Collins)

5:05 PM Deep Learning in NOvA - BARBARA YAEGGY (University of Cincinnati)

5:30 PM Transformer Network for Event/Particle Identification and Interpretability at NOvA - Jianming Bian (University of California, Irvine)
6:00 PM
6:00 PM - 7:00 PM
Room: HCI J4
Contributions

6:00 PM 3D-Reconstruction of Tau Neutrinos in LArTPC Detectors - BARBARA YAEGGY (University of Cincinnati)

6:05 PM Transformer models for neutrino event reconstruction with KM3NeT/ORCA115 - Iván Mozún Mateo (LPCCAEN / CNRS_IN2P3)

6:10 PM Search for the 2vECB+ of Xe-124 with the XENONnT experiment - Andrea Paloma Cimental Chávez (University of Zurich)

6:15 PM Enhancing atmospheric background reduction using Convolutional Neural Networks in DSNB searches at Super-Kamiokande Gd - Soniya Samani
Wednesday, June 26, 2024
9:00 AM
9:00 AM - 12:25 PM
Room: HCI J4
Contributions

9:00 AM ML applications in radiological image analysis for cancer research - Lorena Escudero (University of Cambridge)

9:35 AM Topological Event discrimination using Deep Convolutional Neural Networks for the NEXT Experiment - Fabian Kellerer (Universitat de Valencia)

10:00 AM Signal Denoising with Machine Learning for LEGEND Data - Tianai Ye (Queen's University)

11:00 AM Probabilistic Position Reconstruction in the XENONnT Experiment - Sebastian Vetter (Karlsruhe Institute of Technology)

11:25 AM Enhancing event discrimination in LEGEND-200 with transformer - Marta Babicz (University of Zurich)

12:00 PM Anomaly aware machine learning for dark matter direct detection at DARWIN - Andre Scaffidi (SISSA)
12:25 PM Lunch break
Lunch break
12:25 PM - 1:35 PM
1:35 PM
1:35 PM - 5:55 PM
Room: HCI J4
Contributions

1:35 PM Latest results from the KATRIN experiment and insights into the neural network approach - Alessandro Schwemmer (Technical University of Munich, Germany)

2:10 PM End-to-End, Machine-Learning-Based Data Reconstruction Chain for LArTPC detectors - Francois Drielsma (SLAC)

2:45 PM One Neural Network, Two Detector Mediums, Three Detection Regions: Multi-detector Machine Learning with DUNE’s Near Detector Prototype - Jessie Micallef (Institute for AI and Fundamental Interactions (MIT & Tufts))

3:10 PM Michel Electron Reconstruction Using a Novel Deep-Learning-Based Multi-Level Event Reconstruction in ICARUS - Yeon-jae Jwa (SLAC)

3:35 PM Generative Modeling for LArTPC Images - Zeviel Imani (Tufts University / IAIFI)

4:30 PM Deep Generative Models for Neutrino Physics - Radi Radev (CERN)

5:05 PM Machine-Learning-Based Data Reconstruction Chain for the Short Baseline Near Detector - Brinden Carlson (University of Florida)

5:40 PM Public Data Challenge - Kazuhiro Terao (SLAC)
Thursday, June 27, 2024
9:00 AM
9:00 AM - 12:25 PM
Room: HCI J4
Contributions

9:00 AM A novel approach in the Pandora multi-algorithm reconstruction to tackle challenging topologies at DUNE - Maria Brigida Brunetti (University of Warwick)

9:25 AM Machine Learning Approaches to Particle Identification in the DUNE Far Detector - Isobel Mawby (Lancaster University)

9:50 AM NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction - Giuseppe Cerati (Fermilab)

11:00 AM NuGraph3: Towards Full LArTPC Reconstruction using GNNs - Adam Aurisano (University of Cincinnati)

11:25 AM Vertex-finding in a DUNE far-detector using Pandora deep-learning - Andrew Chappell (University of Warwick)

11:50 AM Enhancing Liquid Argon TPCs Performance in Low-Energy Physics Classification Problems with Quantum Machine Learning - Roberto Moretti (INFN - Sezione di Milano Bicocca)
12:25 PM Lunch break
Lunch break
12:25 PM - 1:25 PM
1:25 PM
1:25 PM - 5:55 PM
Room: HCI J4
Contributions

1:25 PM Contrastive Learning for Robust Representations of Neutrino Data - Alex Wilkinson (University College London)

2:00 PM Enhanced Event Reconstruction at Hyper-Kamiokande using Graph Neural Networks and Prospect of the Impact to CP Violation Search - Christine Quach (LLR - CNRS)

2:35 PM A Comprehensive Insight into Machine Learning Techniques in KM3NeT - Jorge Prado González (KM3NeT)

3:00 PM Convolutional Neural Network for track reconstruction and PID in the HA-TPC of ND280 upgrade - Anaelle Chalumeau (LPNHE)

3:25 PM Advancing neutrino interaction reconstruction: a deep learning strategy in highly-segmented dense detectors - Mayeul Aubin (ETH Zurich)

4:30 PM Machine Learning-Assisted Unfolding for Neutrino Cross Section Measurements - Roger Huang (Lawrence Berkeley National Laboratory)

4:55 PM Application of Machine Learning techniques to improve event reconstruction in Super-Kamiokande - Nicola Fulvio Calabria (Dipartimento Interateneo di Fisica "M. Merlin", Politecnico di Bari)

5:20 PM Deep Learning Reconstruction for the CLOUD Experiment - Garrett Wendel (Penn State University)
6:30 PM Conference dinner
Conference dinner
6:30 PM - 9:30 PM
Friday, June 28, 2024
9:00 AM
9:00 AM - 1:30 PM
Room: HCI J4
Contributions

9:00 AM Implicit Neural Representation for Modeling the Photon Transportation in a LArTPC - Patrick Tsang (SLAC)

9:35 AM A differentiable simulator for LArTPCs: from proof-of-concept to real applications - Pierre Granger (APC/CNRS)

10:10 AM Simultaneous high-dimensional calibration with differentiable simulation towards data application - Yifan Chen (SLAC)

11:15 AM Differentiable Physics Emulator for Water Cherenkov Detectors - Junjie Xia (IPMU)

11:40 AM Advancing Detector Calibration and Event Reconstruction in Water Cherenkov Neutrino Detectors with Analytical Differentiable Simulations - César Jesús-Valls (Kavli IPMU, University of Tokyo)

12:05 PM Application of Conformal Inference in High Energy Physics - Jiri Franc (Czech Technical University in Prague)

12:30 PM Empirical fits to inclusive electron-carbon scattering data obtained by deep-learning methods - Beata Kowal (University of Wroclaw)

12:55 PM Uncertainty Propagation in Neutrino Reconstruction Models - Daniel Douglas (SLAC National Accelerator Laboratory)

1:20 PM Closing - Kazuhiro Terao (SLAC)

Choose timezone