Name: Machine Learning Conference for X-Ray and Neutron-Based Experiments, Munich 2024
Start: 2024-04-08T08:00:00+02:00
End: 2024-04-10T19:00:00+02:00
Location: Bürgerhaus Garching

Machine Learning Conference for X-Ray and Neutron-Based Experiments, Munich 2024

from Monday, April 8, 2024 (8:00 AM) to Wednesday, April 10, 2024 (7:00 PM)

Monday, April 8, 2024

8:00 AM

8:00 AM - 9:00 AM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room

9:00 AM

9:00 AM - 9:20 AM
9:20 AM
9:20 AM - 10:30 AM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

9:20 AM Deep learning-based feature detection on 2D X-ray surface scattering data - Alexander Hinderhofer (University of Tübingen)

9:50 AM Adaptive X-Ray Reflectivity Measurements using Deep Reinforcement Learning - Stefan Kowarik (Universität Graz)

10:10 AM Tracking morphological changes during sputter deposition using GISAXS and machine learning - Stephan Roth (DESY / KTH)
10:30 AM Coffee Break
Coffee Break
10:30 AM - 11:00 AM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
11:00 AM
11:00 AM - 1:00 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

11:00 AM Characterizing quantum materials with scattering experiments and machine learning - Mingda Li (Massachusetts Institute of Technology (MIT))

11:30 AM Semi-supervised approaches to determining space groups and Bravais Lattices - William Ratcliff (National Institute of Standards and Technology)

11:50 AM Machine learning assisted automation of single crystal neutron diffraction using ReTIA - Huibo Cao (Neutron Scattering Division, Oak Ridge National Laboratory)

12:10 PM Combined phase contrast imaging and diffraction at extreme conditions for determination of kinetic parameters - Emma Ehrenreich-Petersen (Deutsches Elektronen-Synchrotron DESY)

12:30 PM Fast and reliable crystal structure prediction using random search algorithms and machine learning interatomic potentials - Pol Benítez Colominas (Universitat Politècnica de Catalunya)
1:00 PM Lunch Break
Lunch Break
1:00 PM - 2:30 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
2:30 PM
2:30 PM - 4:20 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

2:30 PM Generative machine learning for scattering and spectroscopy data analysis - Andy Sode Anker (Department of Energy, Danish Technical University, Denmark)

3:00 PM Equivariant Generative Models: Atomic-Scale Representations from Diffraction Patterns - Cibrán López Álvarez (Polytechnic University of Catalonia)

3:20 PM Solving atomic structures by combining analysis of PDF pattern with DFT calculations in machine learning enhanced global optimization - Wilke Dononelli (Universität Bremen)

3:40 PM Signal denoising and active learning for multiplexing spectrometer - Daniel Mazzone (Paul Scherrer Institut)

4:00 PM Active-learning assisted neutron spectroscopy: challenges and perspectives - Marina Ganeva (Forschungszentrum Jülich GmbH, JCNS)
4:20 PM Coffee Break
Coffee Break
4:20 PM - 4:50 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
4:50 PM
4:50 PM - 6:40 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

4:50 PM MLExchange: A Machine Learning Platform for On-the-fly Data Analysis at Scientific User Facilities - Tanny Chavez (Lawrence Berkeley National Laboratory)

5:20 PM Learning many-body potential energy landscape for analysis of neutron scattering data - Gaurav Vishwakarma

5:40 PM Machine-learning tools for efficient analysis of X-ray scattering data from wood - Paavo Penttilä (Aalto University)

6:00 PM Weak-signal extraction enabled by deep-neural-network denoising of diffraction data - Jens Oppliger (University of Zurich)

6:20 PM Machine Learning-Based Reconstruction of Quantitative Compositional Maps in Complex Microstructures: Fusion of Neutron and X-ray Tomography with Raman Analysis - Mahdieh Shakoorioskooie (Applied Materials Group, Laboratory for Neutron Scattering and Imaging at the Paul Scherrer Institute, Forschungsstrasse 111, 5232 Villigen, Switzerland)
Tuesday, April 9, 2024
9:00 AM
9:00 AM - 10:30 AM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

9:00 AM Anomaly detection at an X-ray FEL - Daniel Ratner (Stanford, SLAC National Accelerator Laboratory)

9:30 AM AI & ML at Diamond – One Year On - Tim Snow (Diamond Light Source)

9:50 AM Hermes: A Repository for Autonomous Materials Science - Austin McDannald (NIST)

10:10 AM Optimizing Beamline Performance: The Bayesian Approach - Martin Radtke
10:30 AM Coffee Break
Coffee Break
10:30 AM - 11:00 AM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
11:00 AM
11:00 AM - 1:00 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

11:00 AM Autonomous Soft Matter Discovery using X-ray Scattering - Kevin Yager (Brookhaven National Laboratory)

11:30 AM A machine learning-empowered automatic loop centering software tool for macromolecular crystallography beamlines - Chun Li (Institute of High Energy Physics, Chinese Academy of Sciences)

11:50 AM Optimizing Neutron Diffraction Experiments at the Spallation Neutron Source with Temporal Fusion Transformers: A Frontier for AI-Driven Real-Time Decision Making - Xiaoping Wang (Neutron Scattering Division, Oak Ridge National Laboratory)

12:10 PM Towards Closing the Autonomous Loop at Multiple Facilities: Developing Web-based User Interfaces and Data Infrastructure for Autonomous Experiments and Machine Learning Workflows - Wiebke Koepp (Lawrence Berkeley National Lab)

12:30 PM Autonomous experiments in neutron scattering - David Elliott Perryman (Institut Laue-Langevin, 71 Avenue des Martyrs, 38042 Grenoble, France and Institute of Physics, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland)
1:00 PM Lunch Break
Lunch Break
1:00 PM - 2:30 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
2:30 PM
2:30 PM - 4:00 PM
Room: Bürgerhaus 1 - Bürgerhaus Main ball room
Contributions

2:30 PM Autonomous closed-loop experiments through ML-based online analysis in synchrotron beamlines: A case study in x-ray reflectometry - Linus Pithan (DESY)

3:00 PM Cold, warm, warmer, hot! Impact of distance metrics on autonomous experimentation - Lilo Pozzo (University of Washington)

3:20 PM The NIST Autonomous Formulation Laboratory: Solving Industrial Problems with Multifacility X-Ray and Neutron Scattering and AI - Peter Beaucage (National Institute of Standards and Technology)

3:40 PM Machine Learning for automatic selection of a nanoparticle analytical model for Small Angle X-Ray Scattering data analysis - Nicolas Monge (Xenocs, Université Grenoble Alpes)
4:00 PM
4:00 PM - 4:30 PM
Contributions

4:00 PM Machine Learning applied to Material Science - Alessio Gagliardi (Technical University Munich)
4:30 PM Coffee Break
Coffee Break
4:30 PM - 4:50 PM
4:50 PM Poster Session
Poster Session
4:50 PM - 6:50 PM
Contributions

4:50 PM UNet-based Segmentation of 3D Volumetric microtomography geological samples - Diego bladimir Haro fernandez (unical)

5:10 PM Investigating gold deposition of HiPIMS and dcMS on Polystyrene, Poly-4-vinylpyridine and Polystyrenesulfonicacid - Yusuf Bulut

5:30 PM CrysFieldExplorer: Rapid Optimization of the Crystal Field Hamiltonian - Qianli Ma (Oak Ridge National Laboratory)

5:50 PM Analysis and Segmentation of Nucleus with U-Net - Ayse Erozan

6:10 PM A Study on Minimizing Measurement Time Based on Active Experimentation for Energydispersive X-Ray Diffraction - Alexander Liehr (Institute of Materials Engineering (University of Kassel))

6:30 PM Exploring the limits of the random forest algorithm for the classification of X-ray absorption spectra - Marius Retegan (ESRF)

6:30 PM Machine Learning Approaches on X-ray Scattering Beamline: First results and perspectives - Jean-Sébastien MICHA (Univ. Grenoble Alpes, UMR SyMMES CNRS CEA/IRIG and CRG IF BM32 beamline at ESRF)

6:30 PM KI4D4E: Machine Learning Approach for Digital Volume Correlation in 4D Computed Tomography Data at Synchrotron Radiation Beamlines - Tak Ming Wong (Helmholtz-Zentrum Hereon)

6:30 PM Analyzing collective excitations using implicit neural representations - Sathya Chitturi (SLAC National Accelerator Laboratory)

6:30 PM A method to correct angular distortions in Bragg Coherent X-ray Diffraction Imaging - Huaiyu Chen (Lund University)

6:30 PM In Situ GIWAXS of Slot-Die Coated Perovskite Quantum Dot Thin-Films - Thomas Baier

6:30 PM Supervised Machine Learning Approach for Phase Identification in Neutron and X-ray Powder Diffraction Experiments - Loubna Kadri

6:30 PM Phase behavior of thermo- and photoresponsive diblock copolymers for non-invasive schizophrenic switching - Peiran Zhang (Technical University of Munich, Department of Physics, Garching, Germany)

6:30 PM Energy-Dispersive Detection of X-rays with CMOS Cameras: A Machine Learning Approach - Jonas Baumann (Technical University of Berlin, Institute of Optics and Atomic Physics)

6:30 PM The use of artificial neural networks for the unfolding procedures in neutron activation measurements - Nikola Jovancevic (University of Novi Sad)

6:30 PM Providing datasets to characterize process- or deformation-induced structure formation of polymer materials via in situ synchrotron X-ray experiments - Anna Katharina Sambale (Leibniz-Institut für Polymerforschung Dresden e.V.)

6:30 PM Using machine learning to optimize the crystal volume of protein crystals - Tobias Schrader

6:30 PM Neural Network based reflectometry analysis of liquid-gas interfaces - Svenja Hövelmann

6:30 PM Automatized data analysis for surface XRD - Radik Batraev (Nanolab (Photon Science, DESY))

6:30 PM A Deep Learning approach for Gamma spot removal in CCD-based neutron imaging - Michael Schulz

6:30 PM The small angle neutron scattering instrument KWS1 - Henrich Frielinghaus (JCNS)

6:30 PM Gaussian processes regression for preliminary data evaluation at DNS - Oleksandr Koshchii (JCNS at MLZ, Forschungszentrum Jülich GmbH)

6:30 PM Biopolymer-Templated Deposition of Hierarchical 3D-Structured Graphene Oxide/Gold Nanoparticle Hybrids for Surface-Enhanced Raman Scattering - Yingjian Guo (Deutsches Elektronen-Synchrotron DESY)

6:30 PM Deciphering SASE X-ray Pulse Characteristics with β-Variational Autoencoder Networks - Gesa Goetzke (Gesa)

6:30 PM Hierarchical Bayesian approach for adaptive integration of Bragg peaks in time-of-flight neutron scattering data - Guannan Zhang (Oak Ridge National Laboratory) Viktor Reshniak (Oak Ridge National Laboratory) Xiaoping Wang (Oak Ridge National Laboratory)

6:30 PM In situ GISAXS investigation of sputtering IZO thin film for optoelectronic applications - Huaying Zhong

6:30 PM Tackling Laue pattern solving using neural networks - Tomáš Červeň (Charles University)

6:30 PM EFFECT OF PEROVSKITE NANOCRYSTAL NUCLEATION SEEDS ON MICROSTRUCTURE AND CRYSTALLIZATION PATHWAYS IN ORGANIC-INORGANIC HALIDE PEROVSKITE THIN FILMS - Altantulga Buyan-Arivjikh (Technical University of Munich, TUM School of Natural Sciences, Department of Physics, Chair for Functional Materials)

6:30 PM Machine learning short-range spin correlations in pyrochlore antiferromagnet Gd2Hf2O7 - Jianhui Xu (RWTH Aachen Uni., JCNS)

6:30 PM Machine learning for the generation of virtual histology images from X-ray phase contrast tomography of biodegradable metal bone implants - Sarah Irvine (Helmholtz-Zentrum hereon)

6:30 PM Information theory elements for data analysis - Luis Carlos Pardo Soto (Universitat Politècnica de Catalunya)

6:30 PM A solid-state electrolyte interface layer-amphiphilic polymer/metal composite nanoarray for lithium metal battery - Zhuijun Xu (Technische Universität München)

6:30 PM Deep Live Phase Retrieval for Ptychography - Simon Welker (Universität Hamburg (Signal Processing) / Center for Free-Electron Laser Science (Coherent Imaging Division))

6:30 PM Tuning the bandgap of double perovskite by anion exchange - Zhaonan Jin

6:30 PM Machine Learning-Based Crystal Structure Direct Prediction from Neutron Powder Diffraction - Hao Wang (China Spallation Neutron Source)

6:30 PM Establishing Multi-resolution, Multi-modal Data Fusion of Synchrotron Imaging Modalities at Diamond Light Source - Calum Green (Imperial College London)

6:30 PM Revealing the effect of solvent additive selectivity on the formation kinetics in printed active layers for organic solar cells - Jinsheng Zhang (TUM)

6:30 PM In situ study of morphology evolution of block copolymer templated metal oxide films - Guangjiu Pan (Technical University of Munich, TUM School of Natural Sciences, Department of Physics, Chair for Functional Materials)

6:30 PM Assisting users on model selection in small angle neutron scattering experiments - Jose Robledo (JCNS-2 Forschungszentrum Jülich)

6:30 PM Operando study on structure-activity relationship between electrolyte components and electrochemical performance for all-solid-state lithium-ion batteries - Yingying Yan (Lehrstuhl für Funktionelle Materialien, Physik-Department, TU München)

6:30 PM Using PyDevice to connect Beamline simulations to a controls framework (Bluesky/EPICS) - Max Wyman (Argonne National Laboratory)

6:30 PM Phase retrieval by a conditional Wavelet Flow: applications to near-field X-ray holography - Ritz Aguilar (Helmholtz-Zentrum Dresden-Rossendorf (HZDR))

6:30 PM In situ GISAXS investigation of ternary hybrid diblock copolymer thin films containing two types of magnetic nanoparticles - Christopher Everettt

6:30 PM Machine Learning-based Auto-indexing of Neutron Diffraction Pattern from China Spallation Neutron Source - Rong Du (institute of high energy physics)

6:30 PM Leveraging Automatic Differentiation in Complex Model Fitting - Erik Thiessenhusen (HZDR)

6:30 PM KDSource, an Open-Source Code for the generation of Monte Carlo particle sources using Kernel Density Estimation - Norberto Schmidt (Forschungszentrum Jülich)

6:30 PM AI/ML-supported evaluation of PGAA data - Christian Stieghorst (TUM / FRM II)

6:30 PM Integrating Machine Learning into X-ray Data Analysis: Insights from GRADES at SOLEIL - Emmanuel FARHI (Synchrotron SOLEIL) Anass Bellachehab (Synchrotron SOLEIL)

6:30 PM Exploring the Efficacy of Machine Learning in Interatomic Potentials and Neutron Scattering Spectra Predictions - Taner YILDIRIM (NIST Center for Neutron Research, National Institute of Standards and Technology (NIST))

6:30 PM Mapping the ICSD - William Ratcliff (National Institute of Standards and Technology)

6:30 PM McStas Union simulations of a 15 T magnet and background prediction with Machine Learning - Petroula Karakosta (University of Copenhagen)

6:30 PM Hamiltonian-driven modeling using image-recognition-based neural networks in rare-earth spin systems - Huibo Cao (Oak Ridge National Laboratory)

6:30 PM Online Classification of Diverse Metal Materials Using PGNAA and Machine Learning - Helmand Shayan (Deutsch)

6:30 PM Developments in Event Mode Data Analysis - Phillip Bentley (European Spallation Source ESS)

6:30 PM Metainference simulations to interpret small-angle scattering experiments of non-conventional surfactants - Henrique Musseli Cezar (University of Oslo)

6:30 PM Grazing-Incidence X-ray Scattering Data for Machine Learning of Neural Networks - Julian Heger (Technical University of Munich, TUM School of Natural Sciences, Department of Physics, Chair for Functional Materials)

6:30 PM Providing datasets to characterize process- or deformation-induced structure formation of polymer materials via in situ synchrotron X-ray experiments - Eric Euchler (Leibniz-Institut für Polymerforschung (IPF), Dresden, Germany)

6:30 PM Making photon and neutron open data machine-learning ready: a workshop and a roadmap - Peter Steinbach (Helmholtz-Zentrum Dresden-Rossendorf)

6:30 PM Artificial intelligence methods for synchrotron radiation image and diffraction data analysis - 丽娜赵 (中国科学院高能物理研究所)

6:30 PM ROADMAP: Reflectometry-driven Optimization And Discovery of Membrane Active Peptides - Frank Heinrich (Carnegie Mellon University and NIST Center for Neutron Research)

6:30 PM AI-supported preclassification of GISAXS images: mathematical identity detection by autoencoders - Eric Schaefer (HAW) Volker Skwarek (HAW)

6:30 PM Artificial neural networks, operando X-ray powder diffraction CT and functional devices - Antonis Vamvakeros (Imperial College London / Finden ltd)

6:30 PM Machine learning methods research on predicting protein profile parameters by synchrotron radiation small-angle X-ray scattering - Qingmeng LI

6:30 PM Deep learning based approach for speeding up the extraction of morphological parameters in GISAXS data - Shachar Dan (DESY)

6:30 PM The effect of a sputter-deposited TiOx interface modification layer on perovskite solar cells - Xiongzhuo Jiang (Technical University of Munich, TUM School of Natural Sciences, Department of Physics)

6:30 PM Operando GIWAXS Observation of the Stabled degradation process of Green-solvent Based PBDB-TF-T1: BTP-4F-12 Organic Solar Cells with EH-P as Solid Additive - ZERUI LI (TUM)

6:30 PM Machine Learning-Based Analysis of X-ray Scattering for Characterizing Guadua Bamboo - Enriqueta Noriega Benitez (Aalto University)

6:30 PM Validating the use of Gaussian Process Regression for Adaptive Mapping of Residual Stress Fields - Chris Fancher (Oak Ridge National Laboratory)

6:30 PM Machine Learning-driven Quantification of XRF Data: Integrating Sample Generation and Simulation for Enhanced Analysis - Frank Förste (TU Berlin)

6:30 PM Injectable hydrogels from thermoresponsive tri- and tetrablock terpolymers investigated using scattering methods - Feifei Zheng (Technische Universtität München)

6:30 PM Versatile Inverse Problem Framework - Stefan Häusler (Forschungszentrum Jülich GmbH, JCNS) Egor Vezhlev (Forschungszentrum Jülich GmbH, JCNS) Marina Ganeva (Forschungszentrum Jülich GmbH, JCNS)

6:30 PM Characterization of Mesoporous Zinc Titanate Hybrid Films Using Grazing Incidence Small-angle X-ray Scattering - Yanan Li

6:30 PM Machine Learning (ML)-Assisted Fabrication and Scattering data for Solar Cells - Shuxian Xiong (DESY & TUM)

6:30 PM Enhanced air stability of Tin‑Based Perovskite Solar Cells with Quercetin - Xiaojing Ci (Technische Universität München)

6:30 PM Investigation of detector backlighting and other effects in neutron darkfield images - Ala'a Al-Falahat (Department of Mechanical Engineering, Faculty of Engineering, Mutah University, Al-Karak, Jordan)

6:30 PM Generative models for Inverse Problems: The phase retrieval problem from a single distance intensity measurement - Dawit Hailu (Helmholtz-Zentrum hereon)

6:30 PM Physics Informed Neural Networks for Neutron Transport in Large Sample Prompt-Gamma Activation Analysis - Alexander Jesser (Karlsruher Institut für Technologie)

6:30 PM ALSA: Automatic Laue Sample Aligner - Štěpán Venclík (Charles University)

6:30 PM Strategy to Simulate and Fit 2D GISAXS Patterns of Nanostructured Thin Films - Christine M. Papadakis (Technical University of Munich, TUM School of Natural Sciences)

6:30 PM Conformation of star-like molecular brushes with amphiphilic diblock copolymer side arms - Wenqi Xu (Technical University of Munich, TUM School of Natural Sciences, Soft Matter Physics Group)
7:00 PM Conference Dinner at Gasthof Neuwirt, Garching
Conference Dinner at Gasthof Neuwirt, Garching
7:00 PM - 11:00 PM
Wednesday, April 10, 2024

9:00 AM FRM II Tours: morning slots
FRM II Tours: morning slots
9:00 AM - 1:00 PM
Room: UBA 03 33 - Seminar room
Analyzing Large Grazing-Incidence X-Ray Scattering Datasets Using INSIGHT
Analyzing Large Grazing-Incidence X-Ray Scattering Datasets Using INSIGHT
9:00 AM - 1:00 PM
Room: UYM 03 30 - Meeting room (Geb. Ost)
Contributions

9:00 AM Analyzing Large Grazing-Incidence X-Ray Scattering Datasets Using INSIGHT - Lennart Reb (TUM E13)
10:00 AM DARTS: The Data Analysis Remote Treatment Service: AI demo
DARTS: The Data Analysis Remote Treatment Service: AI demo
10:00 AM - 1:00 PM
Room: UYW 04 44 - Seminar room
Contributions

10:00 AM DARTS: The Data Analysis Remote Treatment Service: AI demo - Emmanuel FARHI (Synchrotron SOLEIL)
10:15 AM Machine Learning Basics
Machine Learning Basics
10:15 AM - 1:00 PM
Room: UYG 02 22 - Pforte
Contributions

10:15 AM Machine Learning Basics I - Marina Ganeva (JCNS at MLZ, Forschungszentrum Jülich GmbH) Neelima Paul (Technical University of Munich, Heinz Maier-Leibnitz Zentrum (MLZ)) Stefan Häusler (Forschungszentrum Jülich GmbH, JCNS)
1:00 PM Lunch for workshop participants
Lunch for workshop participants
1:00 PM - 1:30 PM

1:30 PM Afternoon tours
Afternoon tours
1:30 PM - 5:30 PM
Room: UBA 03 33 - Seminar room
Machine Learning basics: part II
Machine Learning basics: part II
1:30 PM - 4:00 PM
Room: UYG 02 22 - Pforte
Contributions

1:30 PM Machine Learning Basics II - Marina Ganeva (JCNS at MLZ, Forschungszentrum Jülich GmbH) Neelima Paul (Technical University of Munich, Heinz Maier-Leibnitz Zentrum (MLZ)) Stefan Häusler (Forschungszentrum Jülich GmbH, JCNS)
spear_tools: Deep learning allrounder for free-electron-laser pulse characterization
spear_tools: Deep learning allrounder for free-electron-laser pulse characterization
1:30 PM - 4:00 PM
Room: UYL 03 22a/b - JCNS Meeting room
Contributions

1:30 PM spear_tools: Deep learning allrounder for free-electron-laser pulse characterization - Kristina Dingel (Intelligent Embedded Systems, University of Kassel) Thorsten Otto (Deutsches Elektronen-Synchrotron DESY)