Name: Artificial Intelligence Applied to Photon and Neutron Science
Start: 2019-11-12T09:00:00+01:00
End: 2019-11-14T14:00:00+01:00
Location: No location set

Artificial Intelligence Applied to Photon and Neutron Science

from Tuesday, November 12, 2019 (9:00 AM) to Thursday, November 14, 2019 (2:00 PM)

Monday, November 11, 2019
Tuesday, November 12, 2019

11:00 AM Registration and cocktail lunch ESRF: entrance hall
Registration and cocktail lunch ESRF: entrance hall
11:00 AM - 1:00 PM
1:40 PM Chairman Dr. Rudolf Dimper
Chairman Dr. Rudolf Dimper
1:40 PM - 3:40 PM
Contributions

1:40 PM Welcome from ESRF Director - Francesco Sette

1:50 PM Welcome from ILL Director - Mark Johnson

2:00 PM Introduction to Machine Learning and Deep Neural Networks for scattering science - Bill Triggs (LJK Grenoble)

2:50 PM Improving data analysis using artificial intelligence: an ESRF perspective - Vincent Favre-Nicolin (ESRF)

3:15 PM Machine learning applications for Small Angle X-ray Scattering data collection and analysis at EMBL-Hamburg - Daniel Franke (EMBL)
3:40 PM

3:40 PM - 4:00 PM
4:00 PM Chairman Dr. Tony Hey
Chairman Dr. Tony Hey
4:00 PM - 6:30 PM
Contributions

4:00 PM DOE's Center for Advanced Mathematics for Energy Research Applications (CAMERA): Artificial Intelligence, Machine Learning, and Experimental Facilities: Present and Future - Jamie Sethian (LBNL/UC Berkeley)

4:50 PM Machine Learning at ILL - Paolo Mutti

5:15 PM Machine learning algorithms for image processing in CryoEM - Carlos Oscar Sorzano (CNB Madrid)

5:40 PM Machine learning and artificial intelligence in MX - Melanie Vollmar (Diamond Light Source)

6:05 PM Convolutional neural networks for DESY photon science - Philipp Heuser (DESY)
7:00 PM

7:00 PM - 9:00 PM
Wednesday, November 13, 2019
9:00 AM Chairman Dr. Paolo Mutti
Chairman Dr. Paolo Mutti
9:00 AM - 10:40 AM
Contributions

9:00 AM Biomedical image reconstruction: From the foundations to deep neural networks - Michael Unser (EPFL)

9:50 AM Machine Learning for improving image quality in tomography - Allard Hendriksen (CWI)

10:15 AM What does artificial intelligence see in 3D protein structures? - Sergei Grudinin (Inria/CNRS)
10:40 AM Group Photo
Group Photo
10:40 AM - 11:00 AM
11:00 AM Chairman Dr. Paolo Mutti
Chairman Dr. Paolo Mutti
11:00 AM - 12:40 PM
Contributions

11:00 AM Data-driven Materials Discovery for Functional Applications - Jacqui Cole (University of Cambridge/ISIS)

11:25 AM Applications of Artificial Neural Networks in Electron Microscopy - Christoph Koch (HU Berlin)

11:50 AM Deep learning for classifying and sorting diffraction images - Julian Zimmermann (Max-Born-Institut für Nichtlineare Optik und Kurzzeitspektroskopie)

12:15 PM PyFitit: the software for quantitative analysis of XANES spectra using machine-learning algorithms - Alexander Guda (The Smart Materials Research Institute, Southern Federal University)
12:40 PM

12:40 PM - 2:00 PM
2:00 PM Chairman Dr. Andy Gotz
Chairman Dr. Andy Gotz
2:00 PM - 3:40 PM
Contributions

2:00 PM Machine learning for an XFEL accelerator - Daniel Ratner (SLAC)

2:50 PM Machine Learning at Argonne National Lab - Stefan Wild (ANL)

3:15 PM Scientific Machine Learning Benchmarks - Jeyan Thiyagalingam (SCD RAL)
3:40 PM

3:40 PM - 4:00 PM
4:00 PM Chairman Dr. Andy Gotz
Chairman Dr. Andy Gotz
4:00 PM - 6:05 PM
Contributions

4:00 PM Machine Learning for accelerating understanding from Neutron Scattering Data - Garrett E. Granroth (ORNL)

4:25 PM Machine Learning at Diamond Light Source: Past, Present and Future - Mark Basham (DLS)

4:50 PM Big Data Science Center at the Shanghai Synchrotron Radiation Facility - The first Superfacility Platform in China - Alessandro Sepe (SSRF)

5:15 PM Deep learning for small angle scattering under grazing incidence - Marina Ganeva (JCNS / MLZ)

5:40 PM Towards automated analysis for neutron reflectivity - Daniil Mironov (STFC)
6:30 PM Aperitif & Dinner
Aperitif & Dinner
6:30 PM - 9:30 PM
Thursday, November 14, 2019
9:00 AM Chairman Dr. Miguel Gonzalez
Chairman Dr. Miguel Gonzalez
9:00 AM - 10:40 AM
Contributions

9:00 AM Deriving the big picture from huge spatial datasets: How to make a little training data go a long way - Joel Saltz (Stony Brook University)

9:50 AM Deep Generative Models for detector simulation - Sofia Vallecorsa (CERN)

10:15 AM Deep learning for Synchrotron X-ray Imaging - Xiaogang Yang (DESY)
10:40 AM

10:40 AM - 11:00 AM
11:00 AM Chairman Dr. Miguel Gonzalez
Chairman Dr. Miguel Gonzalez
11:00 AM - 11:50 AM
Contributions

11:00 AM Machine learning accelerated analysis of materials data: The Smart facility - Keith Butler (SCD RAL)

11:25 AM Machine Learning for Spectroscopy: From Spectra to Atomic Structures - Marius Retegan (ESRF)
11:50 AM

11:50 AM - 12:40 PM