Degrees and Honours
M.Sc. (Technical Universiy of Budapest)
Ph.D. (Hungarian Academy of Science)
Senior Member of IEEE
My general research interests are communication and information theory. More specifically, I am mostly interested in problems of source coding, vector quantization, and data compression. Here one main objective is the theoretical analysis and development of source coding algorithms which can adapt to changing source statistics and/or are robust to channel transmission errors. My recent research efforts concentrate on universal and adaptive vector quantization, high-resolution quantization theory, rate-distortion theory, vector quantizer design, quantization using perceptual distortion measures, joint source-channel coding, robust source coding in networks.
I am also interested in pattern recognition and machine learning. Here my research concentrates on the very interesting interconnection between statistical learning theory and source coding (vector quantization). I also study methods of complexity regularization in neural networks for function learning and new methods of nonlinear principal component analysis with applications to data compression.