A-list-of-expertise,-type-of-data,-and-needs-of-the-network's-members.md

 | Name (Last, First), mail | FZJ Institute/Group | Your ML expertise | Your type of data | Your needs | 
 |:---|:---|:---|:---|:---|
+| 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 |
 | Axer, Markus m.axer@fz-juelich.de | INM-1 Fiber Architecture Group | none | Microscopic resolution 2D and 3D images, scalar and vector valued data | 
 | Comito, Claudia c.comito@fz-juelich.de | JSC - Helmholtz Analytics Framework (HAF) | Currently human-learning |  | Probabilistic approach | 
 | 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 | | |
 | 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 | 
 | 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 | 
+| 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 |
 | Grießbach, Sabine s.griessbach@fz-juelich.de | JSC SimLab Climate Science | none | satellite data, infrared spectra, meteorological data | unsupervied ML | 	
 |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 | 
 | Herten, Andreas a.herten@fz-juelich.de | JSC NVIDIA Application Lab | Software installation | | Overview/support of ML/DL software in Jülich |	
@@ -13,9 +15,7 @@
 | Kraus, Jiri jkraus@nvidia.com | NVIDIA | | | Want to learn the ML/DL needs of scientist at FZJ | 
 | Hagemeier, Björn b.hagemeier@fz-juelich.de | JSC Project Helmholtz Analytics Framework | Basic ML methods | | | |
 | 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 |
-| 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 |
 | Pleiter, Dirk d.pleiter@fz-juelich.de | JSC Technology Department | Architectures optimized for DL, requirements analysis | | |
-| 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 |
 | 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 | |
 |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 | 
 |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 |