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

@@ -17,6 +17,5 @@ Dickscheid, Timo t.dickscheid@fz-juelich.de |	INM-1 Big Data Analytics Group (BD
 | 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 | 
+|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 |  |