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Home arrow Departments arrow Theoretical Methods arrow Department Staff arrow Rosipal, Roman, Ing. Mgr. PhD
Rosipal, Roman, Ing. Mgr. PhD

Tel.: +421 2 591045 32, Room: 505, E-mail: This email address is being protected from spam bots, you need Javascript enabled to view it  

picture-roman

Information Page of SAS Employee

Roman Rosipal, SAS

Address

Dr. Roman Rosipal
Institue of Measurement Science
Slovak Academy of Sciences
Dubravska cesta 9
841 04 Bratislava, Slovak Republic
For more information and papers downloading see the personal webpage

Professional Experience & Research Stays

  • 01/2010 - 03/2011 Section for Artificial Intelligence; Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
  • 10/2007 - 12/2009 Institute of Medical Cybernetics and Artificial Intelligence, Center for Brain Research, Medical University of Vienna, Austria
  • 11/2004 - 09/2007 - Austrian Research Institute for Artificial Intelligence, Vienna, Austria
  • 10/2001 - 11/2004 - NASA Ames Research Center, Computational Sciences Division, Moffett Field, CA, USA
  • 07/2000 - 08/2000 - Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako-Shi, Japan
  • 04/1998 - 06/1998 - Department of Medical Cybernetics and Artificial Intelligence, University of Vienna, Vienna, Austria
  • 01/1996 - present - Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovakia
  • 10/1994 - 12/1995 - Institute of Bionics, Bratislava, Slovakia

Education

  • 2001 - PhD. in computer science,
    University of Paisley, Computing and Information Systems, Paisley, UK
  • 1999 - MSc. in mathematics (Probability and Mathematical Statistics & Numerical Analysis and Optimization),
    Comenius University, Faculty of Mathematics and Physics, Bratislava, Slovakia
  • 1993 - MSc. in electrical engineering,
    Czech Technical University, Faculty of Electrical Engineering, Prague, Czech Republic

Research Interests

  • research in the area of computational and cognitive neuroscience 
  • theoretical and algorithmic aspects of machine learning and applied statistics 
  • analysis of EEG; event-related potentials; modelling and monitoring of the sleep process, cognitive and mental fatigue, attention, vigilance; brain-computer interface

Selected Publications 

  • Trejo L.J., Kubitz K., Rosipal R., Kochavi R.L., Montgomery L.D. EEG-Based Estimation and Classification of Mental Fatigue. Psychology, 6:572-589, 2015.
  • Rosipal R., Lewandowski A., Dorffner G. In search of objective components for sleep quality indexing in normal sleep. Biological Psychology, 94(1):210-220, 2013.
  • Lewandowski A., Rosipal R., Dorffner G. On the Individuality of Sleep EEG Spectra. Journal of Psychophysiology, 27(3):105-112, 2013.
  • Lewandowski A., Rosipal R., Dorffner G. Extracting more information from EEG recordings for a better description of sleep. Computer Methods and Programs in Biomedicine, 108(3):961-972, 2012.
  • Rosipal R. Nonlinear Partial Least Squares: An Overview. In Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, Lodhi H., Yamanishi Y. (eds.), ACCM, IGI Global, pp. 169–189, 2011.
  • Rosipal R., Trejo L. J., Nunez P. L. Application of Multi-way EEG Decomposition for Cognitive Workload Monitoring. In Proceedings of the 6th International Conference on Partial Least Squares and Related Methods, Vinzi V. E, Tenenhaus M., Guan R. (eds.), Beijing, China, pp. 145–149, 2009. 
  • Rosipal R., Peters B., Kecklund G., Åkerstedt T., Gruber G., Woertz M., Anderer P., Dorffner G. EEG-based Drivers' Drowsiness Monitoring using a Hierarchical Gaussian Mixture Model. In Proceedings of 13th International Conference on Human Computer Interaction, Schmorrow D.D., Reeves L.M.(eds.): Augmented Cognition, HCII 2007, Beijing, China, Springer, pp. 294-303, 2007.
  • Trejo, L.J., Rosipal, R., Matthews, B.: Brain-Computer Interfaces for 1-D and 2-D Cursor Control: Designs using Volitional Control of the EEG Spectrum or Steady-State Visual Evoked Potentials. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14(2):225-229, 2006.
  • Rosipal, R., Krämer, N.: Overview and Recent Advances in Partial Least Squares. In Subspace, Latent Structure and Feature Selection Techniques. Saunders C., Grobelnik M., Gunn S., Shawe-Taylor J. (eds.), Springer, 34-51, 2006.
  • De Bie, T., Cristianini, N., Rosipal, R.: Eigenproblems in Pattern Recognition.
    In Handbook of Geometric Computing: Applications in Pattern Recognition, Computer Vision, Neuralcomputing, and Robotics. Bayro-Corrochano E. (eds.), Springer, 129-170, 2005.
  • Rosipal R., Trejo L.J., Matthews B.: Kernel PLS-SVC for Linear and Nonlinear Classification. In Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003), 640-647, Washington DC, 2003.
  • Trejo L.J., Wheeler K.R., Jorgensen C.C., Rosipal R., Clanton S.T., Matthews B., Hibbs A.D., Matthews R., Krupka M.: Multimodal Neuroelectric Interface Development. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11(2):199-204, 2003.
  • Rosipal R., Trejo L.J.: Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space. Journal of Machine Learning Research, 2(Dec):97-123, 2001.
  • Rosipal R., Girolami M.: An Expectation-Maximization Approach to Nonlinear Component Analysis. Neural Computation, 13(3):505-510,2001.

 
 
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