Heinz Koeppl: Difference between revisions
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Heinz got his M.Sc. in Physics from Graz Karl-Franzens University, Austria and his Ph.D. in Electrical Engineering and Information Technology from Graz University of Technology. He is currently a PostDoc at University of California Berkeley, Department of Electrical Engineering and Computer Sciences. In collaboration with Prof. Leon Chua he works on Adaptive Cellular Nonlinear Networks for signal processing applications. | Heinz got his M.Sc. in Physics from Graz Karl-Franzens University, Austria and his Ph.D. in Electrical Engineering and Information Technology from Graz University of Technology. He is currently a PostDoc at University of California Berkeley, Department of Electrical Engineering and Computer Sciences. In collaboration with Prof. Leon Chua he works on Adaptive Cellular Nonlinear Networks for signal processing applications. | ||
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* Emergent behavoir, Local Interaction, Pattern Formation | * Emergent behavoir, Local Interaction, Pattern Formation | ||
* PCA, ICA, Blind Source Separation, Cocktail Party Effect | * PCA, ICA, Blind Source Separation, Cocktail Party Effect | ||
* Multiagent, Reinforcement Learning for Coupled Dynamical Systems | |||
* Application of System Theory and Control Theory in Systems Biology | * Application of System Theory and Control Theory in Systems Biology | ||
* Reverse Engineering of Biological Systems | * Reverse Engineering of Biological Systems | ||
Latest revision as of 01:31, 6 June 2006
Heinz got his M.Sc. in Physics from Graz Karl-Franzens University, Austria and his Ph.D. in Electrical Engineering and Information Technology from Graz University of Technology. He is currently a PostDoc at University of California Berkeley, Department of Electrical Engineering and Computer Sciences. In collaboration with Prof. Leon Chua he works on Adaptive Cellular Nonlinear Networks for signal processing applications.
The background from his Ph.D. research is in nonlinear control systems, especially identification (or reverse engineering) of weakly nonlinear systems.
The current research involves adaptive dynamical units on a regular grid that are only locally coupled. The task is, based on a predetermined global information theoretic objective function (e.g. information rate) for the input-output processing of the grid, find the local adaptation rules for the individual units, such that the grid's emergent dynamics is optimal with respect to the objective function.
Some keywords for his research interest:
- Robust, Fault-Tolerant Engineering Systems
- Emergent behavoir, Local Interaction, Pattern Formation
- PCA, ICA, Blind Source Separation, Cocktail Party Effect
- Multiagent, Reinforcement Learning for Coupled Dynamical Systems
- Application of System Theory and Control Theory in Systems Biology
- Reverse Engineering of Biological Systems