Neutrino Physics and Machine Learning (NPML)

from Friday, 10 July 2020 (10:00) to Friday, 24 July 2020 (17:00)


        : Sessions
    /     : Talks
        : Breaks
10 Jul 2020
14 Jul 2020
21 Jul 2020
22 Jul 2020
24 Jul 2020
AM
10:00
Day 1 Morning - Kazuhiro Terao (SLAC) Marco Del Tutto (Fermilab) (until 12:15) ()
10:00 Introduction - Kazuhiro Terao (SLAC) Taritree Wongjirad (Tufts University) Marco Del Tutto (Fermilab) Corey Adams (Argonne National Laboratory) Adam Aurisano (University of Cincinnati) Nick Prouse (TRIUMF) Jianming Bian (University of California, Irvine) Patrick de Perio (TRIUMF)   ()
10:10 Welcome: High Energy Physics and Machine Learning - Dr Michael Cooke (U.S. Department of Energy)   ()
10:25 White paper introduction - Adam Aurisano (University of Cincinnati)   ()
10:45 DL In MicroBooNE - Taritree Wongjirad (Tufts University)   ()
11:25 Using Sparse Convolutional Neural Networks in MicroBooNE - Ran Itay (WEIZMANN INST.)   ()
11:50 A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE LArTPC - Rui An (Illinois Institute of Techonology)   ()
10:00
Day 2 Morning - Kazuhiro Terao (SLAC) Dr Wouter Van De Pontseele (Harvard University) (until 12:05) ()
10:00 Graph Neural Networks for Reconstruction in Liquid Argon Time Projection Chambers - Dr Jeremy Hewes (University of Cincinnati)   ()
10:25 Graph neural networks for 3D voxel classification in scintillator-based trackers - Mr Saul Alonso Monsalve (CERN)   ()
10:50 Normalizing flows applications in neutrino physics: likelihood-free inference and efficient Monte Carlo generation - Sebastian Pina-Otey (IFAE/Grupo AIA)   ()
11:15 Machine Learning Applications for Reactor Antineutrino Detection at PROSPECT - Andrea Delgado (Oak RIdge National Laboratory)   ()
10:00
Day 3 Morning - Taritree Wongjirad (Tufts University) Patrick de Perio (TRIUMF) (until 12:20) ()
10:00 DIDACTS (Data-Intensive Discovery Accelerated by Computational Techniques for Science) - Aaron Higuera (Rice University)   ()
10:40 Demonstration of background rejection using deep neural networks in the NEXT experiment - Dr Marija Kekic (IGFAE)   ()
11:05 NEXT Ton-Scale Sensitivity using Sparse Convolutional Neural Networks - Katherine Woodruff (University of Texas at Arlington)   ()
11:30 Simulation and Calibration of light response in nEXO detector using machine learning - Mr Prakash Gautam (Drexel University)   ()
11:55 Uncertainty estimation for Deep Learning in Neutrino Physics - Dr Aashwin Mishra (SLAC)   ()
10:00
Day 4 Morning - Kazuhiro Terao (SLAC) Jianming Bian (University of California, Irvine) (until 12:25) ()
10:00 Deep learning in DUNE - Saul Alonso Monsalve (CERN)   ()
10:40 Neutrino energy reconstruction with a regression CNN in the DUNE far detector - Dr Wenjie Wu (University of California, Irvine)   ()
11:05 Estimating the Impact of Neutrino Interaction Mismodeling in DUNE with Multivariate Event Reweighting - Cristovao Vilela (Stony Brook University)   ()
11:30 Enhancing Neutrino Event Reconstruction with Pixel-Based 3D Readout for Liquid Argon Time Projection Chambers - Dr Marco Del Tutto (Fermilab)   ()
10:00
Day 5 Morning - Taritree Wongjirad (Tufts University) Kazuhiro Terao (SLAC) (until 11:55) ()
10:00 Machine Learning based reconstruction for Hyper Kamiokande - Lukas Berns (Tokyo Institute of Technology)   ()
10:40 Inverse Beta Decay Reconstruction in Super-Kamiokande with CNNs - Alexander Goldsack (University of Oxford/Kavli IPMU)   ()
11:05 ML Methods Investigation for Hyper-K Neutron Capture Classification - Matthew Stubbs (University of Winnipeg)   ()
11:30 A Generative Neural Network for Water Cherenkov Reconstruction - Cristovao Vilela (Stony Brook University)   ()
PM
13:00
Day 1 Afternoon - Taritree Wongjirad (Tufts University) Adam Aurisano (University of Cincinnati) (until 15:35) ()
13:00 ML challenges in Theia and WBLS - Dr Björn Wonsak (University of Hamburg)   ()
13:40 Scalable, End-to-End Deep Learning Based Data Reconstruction Chain for 3D Particle Imaging Detectors - Francois Drielsma (SLAC)   ()
14:20 Scalable 3D Semantic Segmentation and Point Proposal Network for large-scale high resolution particle imaging detectors - Laura Domine (Stanford University)   ()
14:45 Proposal-free Deep Sparse Convolutional Neural Network for 3D Pixel Clustering - Dae Koh (SLAC)   ()
15:10 Enabling A Deep Neural Networks based 3D LArTPC Data Reconstruction Chain for ICARUS - Patrick Tsang (SLAC)   ()
13:00
Day 2 Afternoon - Marco Del Tutto (Fermilab) Corey Adams (Argonne National Laboratory) (until 15:25) ()
13:00 Summary of Machine Learning Applications for the COHERENT Collaboration - Jacob Daughhetee (University of Tennessee)   ()
13:40 A Machine Learning Approach to Study the Neutrino Charged-current Interaction on 127I - Mr Peibo An (Duke University)   ()
14:05 Machine Learning Techniques in Event Reconstruction and Classification for Cyclotron Radiation Emission Spectroscopy Signals in Project 8 - Mr Luis Saldaña (Yale University)   ()
14:45 The deep learning frontiers of KamLAND-Zen - Aobo Li (Boston University)   ()
13:00
Day 3 Afternoon - Corey Adams (Argonne National Laboratory) Adam Aurisano (University of Cincinnati) (until 14:55) ()
13:00 Machine Learning in the NOvA Experiment - Karl Warburton (Iowa State University)   ()
13:40 Regression CNNs for Energy Reconstruction in the NOvA Experiment - Ben Jargowsky (University of California, Irvine)   ()
14:05 Neutrino Energy Reconstruction with Recurrent Neural Networks at NOvA - Dmitrii Torbunov (University of Minnesota, Twin Cities)   ()
14:30 Full Event Reconstruction on NOvA using Instance Segmentation - Micah Groh (Indiana University Bloomington)   ()
13:00
Day 4 Afternoon - Patrick de Perio (TRIUMF) Kazuhiro Terao (SLAC) (until 15:25) ()
13:00 Machine learning techniques in ANNIE - Dr Evangelia Drakopoulou (University of Edinburgh)   ()
13:40 GPU as a Service for Accelerating Machine Learning Applications in the Reconstruction Workflows of Neutrino Experiments - Tingjun Yang (Fermilab)   ()
14:05 Scalable, Distributed Machine Learning¶ - Corey Adams (Argonne National Laboratory)   ()
13:00
Day 5 Afternoon - Nick Prouse (TRIUMF) Patrick de Perio (TRIUMF) (until 15:05) ()
13:00 Machine Learning Research and Applications in IceCube - Mirco Huennefeld (TU Dortmund)   ()
13:40 Deep Learning Classifier for Low-Energy Events in IceCube - Maria Prado Rodriguez (University of Wisconsin-Madison)   ()
14:05 Optimizing a CNN to Reconstruct Low Energy IceCube Neutrino Events - Jessie Micallef (Michigan State University)   ()
14:30 White paper discussion - Adam Aurisano (University of Cincinnati)   ()
14:50 Closing - Kazuhiro Terao (SLAC)   ()