Name: Neutrino Physics and Machine Learning (NPML): Lightning Talks
Start: 2020-06-17T10:00:00-05:00
End: 2020-06-19T16:00:00-05:00
Location: No location set

Neutrino Physics and Machine Learning (NPML): Lightning Talks

from Wednesday, June 17, 2020 (10:00 AM) to Friday, June 19, 2020 (4:00 PM)

Monday, June 15, 2020
Tuesday, June 16, 2020
Wednesday, June 17, 2020
10:30 AM Introduction
Introduction
10:30 AM - 10:45 AM
Contributions

10:30 AM Introduction - Kazuhiro Terao (SLAC)
10:45 AM Lightning Talks
Lightning Talks
10:45 AM - 12:00 PM
Contributions

10:45 AM Development of a BDT-based multi-ring sample at the T2K far detector - Trevor Towstego (University of Toronto)

11:00 AM A Machine Learning Approach to Study the Neutrino Charged-current Interaction on 127I - Peibo An (Duke University)

11:15 AM Using Sparse Convolutional Neural Networks in MicroBooNE - Ran Itay (WEIZMANN INST.)

11:30 AM Detection of Cosmic Muon Spallation Background in LS-Detector Using Machine Learning - Zhenghao Fu (MIT)
12:00 PM

12:00 PM - 1:00 PM
1:00 PM Lightning Talks
Lightning Talks
1:00 PM - 2:30 PM
Contributions

1:00 PM A Convolutional Neural Network for Shower Energy Reconstruction in MicroBooNE - Nicholas Kamp

1:15 PM Machine Learning Applications for Reactor Antineutrino Detection at PROSPECT - Andrea Delgado (Oak RIdge National Laboratory)

1:30 PM Using Convolutional Neural Network for Pulse Shape Discrimination in Liquid Argon - Jacob Daughhetee (University of Tennessee)

1:45 PM Reconstructing 10 GeV-Scale Neutrino Events in IceCube using CNNs - Jessie Micallef (Michigan State University)

2:00 PM Reconstructing Michel Electrons in ICARUS with Deep Neural Networks - Laura Domine (Stanford University)

2:15 PM Particle Clustering in LArTPCs with Embedding Learning Convolutional Neural Networks - Dae Koh (SLAC)
Thursday, June 18, 2020
Friday, June 19, 2020
10:30 AM Lightning Talks
Lightning Talks
10:30 AM - 12:00 PM
Contributions

10:30 AM Modeling Vector and Axial Nucleon Form Factors with Bayesian Neural Networks - Graczyk Krzysztof ( Institute of Theoretical Physics, Wroclaw University )

10:45 AM Clustering Cosmic Muon and Neutrino Interactions in MicroBooNE using a Deep Convolutional Neural Network - Joshua Mills (MicroBooNE)

11:00 AM Using a Convolutional Neural Network to Reconstruct Dead Channels in MicroBooNE - Katie Mason (Tufts University)

11:15 AM Learning from Data: the Zen of Deep Learning in KamLAND - Aobo Li (Boston University)

11:30 AM A Convolutional Neural Network for Multiple Particle Identification in the MicroBooNE LArTPC - Rui An (Illinois Institute of Techonology)
12:00 PM

12:00 PM - 1:00 PM
1:00 PM Lightning Talks
Lightning Talks
1:00 PM - 2:15 PM
Contributions

1:00 PM Reconstructing 3D charge positions in LArTPCs using a CNN - Ralitsa Sharankova (Tufts University)

1:15 PM Efficient neutrino oscillation parameter inference using Gaussian processes - Nitish Nayak (University of California-Irvine)

1:30 PM Shower Reconstruction in Liquid Argon Time Projection Chambers using Graphical Neural Networks - Francois Drielsma (SLAC)

1:45 PM Interaction Clustering in Liquid Argon Time Projection Chamber using Graph Neural Networks - Qing Lin (SLAC)

2:00 PM Sparse Segmentation for Particle ID in ProtoDUNE - Carlos s Sarasty Segura (University of Cincinnati)
2:15 PM Closing
Closing
2:15 PM - 2:30 PM
Contributions

2:15 PM Close out - Adam Aurisano (University of Cincinnati) Corey Adams (Argonne National Laboratory) Jianming Bian (University of California-Irvine) Kazuhiro Terao (SLAC) Marco Del Tutto (Fermilab) Nick Prouse (TRIUMF) Patrick de Perio (TRIUMF) Taritree Wongjirad (Tufts University)

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