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| Name (Last, First), mail | FZJ Institute/Group | Your ML expertise | Your type of data | Your needs |
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| Arasan, Durai d.arasan@fz-juelich.de | INM-1 Connectivity | Support Vector Machines, Random Forests, Neural Networks | 3D MRI data | Developing ML algorithms for neuroimaging data, Learning Deep Learning, feature engineering and optimization |
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| Axer, Markus m.axer@fz-juelich.de | INM-1 Fiber Architecture Group | none | Microscopic resolution 2D and 3D images, scalar and vector valued data |
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| Comito, Claudia c.comito@fz-juelich.de | JSC - Helmholtz Analytics Framework (HAF) | Currently human-learning | | Probabilistic approach |
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| Dickscheid, Timo t.dickscheid@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | Deep Learning with ConvNets, Image Segmentation, Image Feature detection, Markov Random Fields, Clustering, Analogies to the human brain| Microscopic resolution 2D and 3D images | | |
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| Gohlke, Holger h.gohlke@fz-juelich.de | JSC / ICS-6 / NIC Research Group | Deep learning / Supervised/unsupervised learning | Molecular structure data | meet ML experts, possibility to discuss individual DL problem |
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| Göbbert, Jens Henrik j.goebbert@fz-juelich.de | JSC Cross-Sectional-Team Visualization | Basic DL with Keras | turbulent flows (3D) | Collaborations/support for enabling DL with on HPC with Jupyter |
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| Goergen, Klaus k.goergen@fz-juelich.de | IBG-3 Integrated Modelling | various supervised and unsupervised methods, PCA, CCA, SOMs; not used recently though | Regional climate model outputs, meteorological observations | big data (200-300TB) capable data analytics frameworks |
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| Grießbach, Sabine s.griessbach@fz-juelich.de | JSC SimLab Climate Science | none | satellite data, infrared spectra, meteorological data | unsupervied ML |
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|Hermanns, Marc-André m.a.hermanns@fz-juelich.de | JSC Cross-Sectional-Team Parallel Performance | none yet (testing with Keras atm.) | Performance Data (profile and trace) | Identify or estimate performance phenomena |
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| Herten, Andreas a.herten@fz-juelich.de | JSC NVIDIA Application Lab | Software installation | | Overview/support of ML/DL software in Jülich |
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| Kraus, Jiri jkraus@nvidia.com | NVIDIA | | | Want to learn the ML/DL needs of scientist at FZJ |
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| Hagemeier, Björn b.hagemeier@fz-juelich.de | JSC Project Helmholtz Analytics Framework | Basic ML methods | | | |
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| Stadtler, Scarlet s.stadtler@fz-juelich.de | JSC Federated Systems and Data Division | Absolute Beginner (At JSC courses in ML and DL) | Meteorological four dimensional Data (space and time) | meet ML experts, possibility to discuss individual DL problems |
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| Goergen, Klaus k.goergen@fz-juelich.de | IBG-3 Integrated Modelling | various supervised and unsupervised methods, PCA, CCA, SOMs; not used recently though | Regional climate model outputs, meteorological observations | big data (200-300TB) capable data analytics frameworks |
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| Pleiter, Dirk d.pleiter@fz-juelich.de | JSC Technology Department | Architectures optimized for DL, requirements analysis | | |
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| Arasan, Durai d.arasan@fz-juelich.de | INM-1 Connectivity | Support Vector Machines, Random Forests, Neural Networks | 3D MRI data | Developing ML algorithms for neuroimaging data, Learning Deep Learning, feature engineering and optimization |
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| Huysegoms, Marcel m.huysegoms@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | Deep Learning with ConvNets, Markov Random Fields, Clustering | Microscopic-resolution 2D and 3D cyto images | |
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|Schultz, Martin m.schultz@fz-juelich.de | JSC-FSD | Deep Learning Timeseries and video-sequence analysis (IntelliAQ project) | Observational time series, numerical weather model data (gridded fields), geodata (gridded fields and point features | discussion forum to exchange experiences with specific architectures and methods, and to share ideas how to improve result |
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|Schiffer, Christian c.schiffer@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | Deep Learning with ConvNets, Image Segmentation, Distributed DL on HPC with TensorFlow, Unsupervised Domain Adaptation | Microscopic resolution 2D images |
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