Florian Steinke

 

 

Welcome to my homepage!

I am working as a research scientist at Siemens Corporate Technology in Munich.

My research interests are in distributed control, machine learning, probabilistic models and optimization, and their application in different domains.

A recent focus of my work is in the energy domain. In this context, I am giving a lecture on Methods for the Analysis and the Control of Smart Grids together with Dr. Michael Metzger in WS 2012/13 at the TU München.

My publications can be found below. If you have any questions regarding my work or if you want to collaborate in any form, do not hesitate to contact me.

 

Publications

 

Journal Articles (11)

 

Steinke, F., P. Wolfrum and C. Hoffmann: Grid vs. storage in a 100% renewable Europe, Renewable Energy 50, 826-832, (2013)

 

Schaber, K., F. Steinke and T. Hamacher: Grid Extensions for the Integration of Variable Renewable Energies in Europe: Who Benefits Where?, Energy Policy 43, 123-135, (2012)

Schaber, K., F. Steinke, P. Mühlich and  T. Hamacher: Parametric study of variable renewable energy integration in Europe: Advantages and costs of transmission grid extensions, Energy Policy 42, 498-508, (2012)

 

E. Della Valle, I. Celino, D. Dell’Aglio, R. Grothmann, F. Steinke and V. Tresp: Semantic Traffic-Aware Routing Using the LarKC Platform, IEEE Internet Computing 15(6), 15-23, (11 2011)

Hofmann, M., I. Bezrukov, F. Mantlik, P. Aschoff, F. Steinke, T. Beyer, B. J. Pichler and B. Schölkopf: MRI-Based Attenuation Correction for Whole-Body PET/MRI: Quantitative Evaluation of Segmentation- and Atlas-Based Methods, Journal of Nuclear Medicine 52(9), 1392-1399, (08 2011)

 

Steinke, F., M. Hein and B. Schölkopf: Non-parametric Regression between General Riemannian Manifolds, SIAM Journal on Imaging Sciences (SIIMS) 3(3), 527-563, (09 2010)

  

Steinke, F. and B. Schölkopf: Kernels, Regularization and Differential Equations. Pattern Recognition 41(11), 3271-3286 (11 2008)

 

Hofmann, M., F. Steinke, V. Scheel, G. Charpiat, J. Farquhar, P. Aschoff, M. Brady, B. Schölkopf and B. J. Pichler: MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration. Journal of Nuclear Medicine 49(11), 1875-1883 (10 2008)
  

Steinke, F., M. Hein, J. Peters and B. Schölkopf: Manifold-valued Thin-plate Splines with Applications in Computer Graphics. Computer Graphics Forum 27(2), 437-448 (04 2008)
  

Steinke, F., M. Seeger and K. Tsuda: Experimental design for efficient identification of gene regulatory networks using sparse Bayesian models. BMC Systems Biology 1(51), 1-15 (11 2007)
  

Steinke, F., B. Schölkopf and V. Blanz: Support Vector Machines for 3D Shape Processing. Computer Graphics Forum 24(3, EUROGRAPHICS 2005), 285-294 (09 2005)
    

Peer-Reviewed Conference Papers (13)

K. Schaber, F. Steinke and  T. Hamacher: Managing Temporary Oversupply from Renewables Efficiently: Electricity Storage Versus Energy Sector Coupling in Germany. 32nd International Energy Workshop (IEW 2013), Paris, France (2013) 

 

J. L. Moore, F. Steinke, and V. Tresp: A Novel Metric for Information Retrieval in Semantic Networks. 3rd International Workshop on Inductive Reasoning and Machine Learning for the Semantic Web (IRMLeS 2011), Heraklion, Greece (2011)

I. Celino, D. Dell'Aglio, E. Della Valle, R. Grothmann, F. Steinke and V. Tresp: Integrating Machine Learning in a Semantic Web Platform for Traffic Forecasting and Routing. 3rd International Workshop on Inductive Reasoning and Machine Learning for the Semantic Web (IRMLeS 2011), Heraklion, Greece (2011) 

D. Magatti, F. Steinke, M. Bundschus and V. Tresp: Combined Structured and Keyword-Based Search in Textually Enriched Entity-Relationship Graphs. First Workshop on Automated Knowledge Base Construction, Grenoble (2010) 
 

T.A. Runkler and F. Steinke: A New Approach to Clustering Using Eigen Decomposition. World Congress on Computational Intelligence (WCCI), International Conference on Fuzzy Systems (FUZZ-IEEE), Barcelona, Spain (2010)
 

K.I. Kim, F. Steinke and M. Hein: Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction. Advances in Neural Information Processing Systems 22: Proceedings of the 2009 Conference, MIT Press, Cambridge, MA, USA (2009)

 

Lee, D., M. Hofmann, F. Steinke, Y. Altun, N. D. Cahill and B. Schölkopf: Learning the Similarity Measure for Multi-Modal 3D Image Registration. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009) (accepted) (06 2009)

 

Steinke, F. and M. Hein: Non-parametric Regression between Riemannian Manifolds. Advances in Neural Information Processing Systems 21: Proceedings of the 2008 Conference, 1561-1568. (Eds.) Koller, D., D. Schuurmans, Y. Bengio, L. Bottou, MIT Press, Cambridge, MA, USA (06 2009)
     

Steinke, F., B. Schölkopf and V. Blanz: Learning Dense 3D Correspondence. Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, 1313-1320. (Eds.) Schölkopf, B., J. Platt, T. Hofmann, MIT Press, Cambridge, MA, USA (09 2007)
  

Seeger, M., F. Steinke and K. Tsuda: Bayesian Inference and Optimal Design in the Sparse Linear Model. Proceedings of the 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007), 444-451. (Eds.) Meila, M., X. Shen, Microtome, Brookline, MA, USA (03 2007)
     

Steinke, F. and B. Schölkopf: Machine Learning Methods For Estimating Operator Equations. Proceedings of the 14th IFAC Symposium on System Identification (SYSID 2006), 1-6. (Eds.) Ninness, B., H. Hjalmarsson, Elsevier, Oxford, United Kingdom (03 2006)
  

Cooke, T., F. Steinke, C. Wallraven and H. H. Bülthoff: A similarity-based approach to perceptual feature validation. Proceedings of the 2nd Symposium on Applied Perception in Graphics and Visualization (APGV‘05), 59-66, ACM Press, New York, NY, USA (08 2005)
  

Schölkopf, B., F. Steinke and V. Blanz: Object correspondence as a machine learning problem. Proceedings of the 22nd International Conference on Machine Learning, 777 - 784. (Eds.) De Raedt, L., S. Wrobel (2005)
  

Technical Reports (2)

VDE Studie: Erneuerbare Energie braucht flexible Kraftwerke – Szenarien bis 2020, (2012)

Hein, M., F. Steinke and B. Schölkopf: Energy Functionals for Manifold-valued Mappings and Their Properties. (167) (01 2008)
  

Abstracts (2)

F. Steinke, K. Schaber, T. Hamacher: Die Netzabhängige Dynamik zukünftiger Elektrizitätsmärkte. ETG-Kongress / Fachtagung Kundenbeteiligung (2011) 

Hofmann, M., F. Steinke, V. Scheel, G. Charpiat, M. Brady, B. Schölkopf and B. J. Pichler: MR-Based PET Attenuation Correction: Method and Validation. 2007 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC 2007) 2007(M16-6), 1-2 (11 2007)
     

Diploma & PhD Theses (2)
 

Steinke, F.: From Differential Equations to Differential Geometry: Aspects of Regularisation in Machine Learning. (05/ 2009)

Steinke, F.: Implicit Surfaces For Modelling Human Heads. (09/ 2005)
 

Talks (8)

 

I. Thien, M. Leuthold, F. Steinke, D. U. Sauer: Speicher- und Netzausbaubedarf in einem europäischen

Elektrizitätsversorgungssystem mit 100% EE-Versorgung, VDE Kongress, Stuttgart (2012)

I. Pyc, F. Steinke, B. Gemsjäger: Scenarios for a Sustainable Decentralized Electricity Generation in

Germany until 2020 and Consequences for Power Plant Operation, VDE Kongress, Würzburg (2011)

F. Steinke, C. Hofmann: Energie System Design – Koppelung von Meteorologie, Geographie und Energiewirtschaft für die Analyse zukünftiger Energiesysteme, 4. Deutsches GeoForum, Berlin, Germany (2011)

 

Hofmann, M., F. Steinke, P. Aschoff, M. Lichy, M. Brady, B. Schölkopf and B. J. Pichler: MR-Based PET Attenuation Correction: Initial Results for Whole Body. Medical Imaging Conference, Dresden, Germany (10 2008)

Steinke, F., M. Hein and B. Schölkopf: Thin-Plate Splines Between Riemannian Manifolds. Workshop on Geometry and Statistics of Shapes 2008, Bonn, Germany (06 2008)
  

Hofmann, M., F. Steinke, V. Scheel, M. Brady, B. Schölkopf and B. J. Pichler: MR-Based PET Attenuation Correction: Method and Validation. Joint Molecular Imaging Conference 2007, Providence, RI, USA (09 2007)
     

Hofmann, M., F. Steinke, M. S. Judenhofer, C. D. Claussen, B. Schölkopf and B. J. Pichler: A Machine Learning Approach for Determining the PET Attenuation Map from Magnetic Resonance Images. IEEE Medical Imaging Conference 2006, San Diego, CA, USA (11 2006)

Hofmann, M., F. Steinke, I. Bezrukov, A. Kolb, P. Aschoff, M. Lichy, M. Erb, T. Nägele, M. Brady, B. Schölkopf and B. J. Pichler: MR-based Attenuation Correction for PET/MR, ISMRM 2009, Honolulu, Hawaii