Name: Reconstruction and Machine Learning in Neutrino Experiments
Start: 2019-09-16T08:45:00+02:00
End: 2019-09-18T13:00:00+02:00
Location: DESY Hamburg

Monday 16 September 2019

08:45

08:45 - 09:10
Room: Building 1b, SR4b
09:10
09:10 - 09:25
Room: Building 1b, SR4b
Contributions

09:10 Welcome and Introduction - Björn Wonsak (UniHH Opera)
09:25 Reconstruction 1
Reconstruction 1
09:25 - 10:15
Room: Building 1b, SR4b
Contributions

09:25 The Pandora particle flow algorithm - Andrew Smith (The University of Cambridge)

09:50 Reconstructing 3D hit information directly from 2D projections - Chris Backhouse (UCL)
10:15 Coffee break
Coffee break
10:15 - 10:45
Room: Building 1b, SR4b

10:45 TRIUMP-Helmholz workshop. Keynote: Perspectives on the Future of Data Intensive Computing
TRIUMP-Helmholz workshop. Keynote: Perspectives on the Future of Data Intensive Computing
10:45 - 11:35
Room: Building 5, Auditorium
11:45 Reconstruction 2
Reconstruction 2
11:45 - 13:00
Room: Building 1b, SR4b
Contributions

11:45 Track Reconstruction and Characterization in Liquid Scintillator Detectors at High Energies - Mikko Meyer (TU Dresden)

12:10 Distributed imaging for liquid scintillation detectors - Jacopo Dalmasson (Stanford University)

12:35 Event reconstruction in JUNO - Wuming Luo (Institute of High Energy Physics, China)
13:00 Lunch
Lunch
13:00 - 14:30
Room: Building 1b, SR4b
14:30 Talks: Reconstruction 3
Talks: Reconstruction 3
14:30 - 16:00
Room: Building 1b, SR4b
Contributions

14:30 TPC Simulation and Signal Processing for LArTPCs - Hanyu Wei (Brookhaven National Laboratory)

14:55 Linear system in LArTPC 3D image reconstruction - Chao Zhang (Brookhaven National Laboratory)

15:20 LArTPC Charge-Light Matching and PID with Wire Cell - Xin Qian (Brookhaven National Laboratory)
16:00 DESY tour
DESY tour
16:00 - 19:00
Room: Building 1b, SR4b
Tuesday 17 September 2019

09:00 TRIUMPF-Helmholz Workshop. Keynote: How to know, where to look - prioritising in computer vision
TRIUMPF-Helmholz Workshop. Keynote: How to know, where to look - prioritising in computer vision
09:00 - 09:40
Room: Building 5, Autitorium
09:50 Talks: Machine Learning 1
Talks: Machine Learning 1
09:50 - 10:45
Room: Building 1b, SR4b
Contributions

09:50 Machine Learning techniques on NOvA - Micah Groh (Indiana University)

10:10 Particle Identification Using Convolutional Neural Networks in the NOvA Experiment - Ryan Murphy (Indiana University)
10:45 Coffee break
Coffee break
10:45 - 11:15
Room: Building 1b, SR4b
11:15 Talks> Machine Learning 2
Talks> Machine Learning 2
11:15 - 12:50
Room: Building 1b, SR4b
Contributions

11:15 Machine Lerning Applications in Minerva - Anushree GHOSH (Universidad Tecnica Federico Santa Maria, Chile) Anushree Ghosh (UTFSM, Chile)

11:55 Event Classification using Neural Networks in DUNE - Saul Alonso-Monsalve (CERN)

12:20 Regression CNN Based Energy and Vertex Reconstruction at DUNE - Jianming Bian (University of California, Irvine)
12:50 Lunch
Lunch
12:50 - 14:20
Room: Building 1b, SR4b
14:20 Talks: Machine Learning 3
Talks: Machine Learning 3
14:20 - 16:00
Room: Building 1b, SR4b
Contributions

14:20 Machine Learning and Computer Vision for Particle Imaging Detectors in Neutrino Experiments - KAZUHIRO TERAO (SLAC National Accelerator Laboratory)

14:45 Machine learning applications for JUNO - Maxim Gromov (SINP MSU, JINR)

15:10 Machine Learning methods in Borexino Experiment - Yu Xu (IKP2 FZJ)

15:35 Applications of the Topological Track Reconstruction to low energy events - Malte Stender (University Hamburg - Institute for experimental physics)
16:00 Coffee break
Coffee break
16:00 - 16:30
Room: Building 1b, SR4b
16:30 Talks: Machinhe Learning 4
Talks: Machinhe Learning 4
16:30 - 18:00
Room: Building 1b, SR4b
Contributions

16:30 Event identification in the NEXT experiment using CNNs - Marija Kekic (IFIC)

16:55 Deep Learning in the EXO-200 experiment - Tobias Ziegler (Erlangen Centre for Astroparticle Physics)

17:20 ML techniques for the GERDA 0nbb experiment and beyond - Oliver Schulz (MPI Munich)
20:00 Social Dinner
Social Dinner
20:00 - 22:00
Room: Building 1b, SR4b
Wednesday 18 September 2019
09:00 Talks: Machine Learning 5
Talks: Machine Learning 5
09:00 - 10:50
Room: Building 1b, SR4b
Contributions

09:00 Deep Learning in KM3NeT - Simona Maria Stellacci (INFN)

09:35 Measurement of Neutrino Energy Spectra via Deconvolution with IceCube - Tim Ruhe (TU Dortmund)

10:15 Image Based Reconstruction and Deep Learning in MicroBooNE - Rui An (Illinois Institute of Technology)
10:50 Coffee break
Coffee break
10:50 - 11:20
Room: Building 1b, SR4b
11:20 Talks: Machine Learning 6
Talks: Machine Learning 6
11:20 - 13:00
Room: Building 1b, SR4b
Contributions

11:20 Particle tracking based on fully unsupervised disentanglement of the geometrical factors of variation - Mykhailo Vladymyrov (University of Bern)

11:45 Machine learning in PET imaging with PETALO - Joshua Renner (Instituto Galego de Fisica de Altas Enerxias (IGFAE) - University of Santiago de Compostela)

12:10 Closing Words, maybe more - Björn Wonsak (UniHH Opera)