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

@@ -18,4 +18,7 @@ Dickscheid, Timo t.dickscheid@fz-juelich.de |	INM-1 Big Data Analytics Group (BD
 | 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 | 
-|Campos, Lucas l.campos@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | None; JSC courses on Machine Learning/Deep Learning. Weekend fun with SVM and Neural networks way back when | 3D MRI data |  | 		
+|Campos, Lucas l.campos@fz-juelich.de | INM-1 Big Data Analytics Group (BDA) | None; JSC courses on Machine Learning/Deep Learning. Weekend fun with SVM and Neural networks way back when | 3D MRI data |  | 
+| Dammers, Jürgen j.dammers@fz-juelich.de | INM-4 MEG Group | A bit of supervised Deep Learning techniques (CNN and DNN) | 4D MEG data | Developing unsupervised deep learning strategies for the analysis of large sets of 4D neuroimaging data | 
+| Cavallaro, Gabriele g.cavallaro@fz-juelich.de | JSC High Productivity Data Processing Group | Supervised learning, Unsupervised learning, Feature engineering | Remote sensing data (optical and SAR) |  | 
+| Axer, Markus m.axer@fz-juelich.de | INM-1 Fiber Architecture Group | none | Microscopic resolution 2D and 3D images, scalar and vector valued data |