Nicolaos B. Karayiannis received the Diploma degree in Electrical Engineering from the National Technical University of Athens in 1983,and the M.A.Sc. and Ph.D.degrees in Electrical Engineering from the University of Toronto in 1987 and 1991, respectively.

He is currently a Professor in the Department of Electrical and Computer Engineering, University of Houston. From 1984 to 1991 he worked as a Research and Teaching Assistant at the University of Toronto. From 1983 to 1984 he was a Research Assistant at the Nuclear Research Center ``Democritos,'' Athens, Greece, where he was engaged in research on multidimensional signal processing. He has published more than 100 papers, including 40 in technical journals, and is the co-author of the book Artificial Neural Networks: Learning Algorithms, Performance Evaluation, and Applications (Kluwer, 1993). He is the recipient of the W. T. Kittinger Outstanding Teacher Award (1994), the College of Engineering Young Faculty Research Excellence Award (1997), and the University of Houston El Paso Energy Foundation Faculty Achievement Award (2000). He is also a co-recipient of a Theoretical Development Award for a paper presented at the Artificial Neural Networks in Engineering '94 Conference. He is an Associate Editor of the IEEE Transactions on Neural Networks and the IEEE Transactions on Fuzzy Systems. He also served as the General Chair of the 1997 International Conference on Neural Networks (ICNN '97), held in Houston, TX, on June 9-12, 1997.

-• Research and Academics

My career goal is to utilize my research experience in a variety of disciplines by leading a research team toward the solution of real-world problems by cross-fertilizing emerging technologies and computational tools. An example of such research is my project "Video Technologies for Neonatal Seizures," which is currently funded by the National Institutes of Health (Grant No: 1 R01 EB00183-01; PI: Karayiannis). The main goal of this project is the development of automated video processing and analysis procedures aimed at the identification and characterization of neonatal seizures. Neonatal seizures are also the focus of the project "Automated Detection of Epileptic Seizures in the Neonatal EEG," which is also funded by the NIH (Grant No: 1 R01 NS040577-01; PI:Glover). The major goal of this project is to develop techniques for computer-automated detection of electroencephalographic seizure activity in the EEG of neonates. As a Co-PI of this project, I am responsible for the development of a modular system for artifact detection.

My dedication to academic research originated from my fascination with the development of novel computational tools that can learn from data. This research area is generally described as computational intelligence. My research focuses on neural network models and neuro-fuzzy systems, including supervised radial basis function (RBF) neural network models and unsupervised leaning vector quantization (LVQ) and clustering algorithms. These computational tools and the associated learning algorithms are evaluated on applications involving pattern clustering and classification as well as applications involving time series analysis (e.g., electric power load forecasting).
My interest in challenging real-world applications is reflected by the third component of my research, which focuses on the development of new solutions to hot problems in communications. The first communication application is the development of efficient subband encoding schemes appropriate for wireless video compression. In this project, spatiotemporal decomposition of video relies on a new non-separable multiresolution analysis. The second communication application is the development and evaluation of entropy-constrained algorithms for routing of communication networks. This project relies on the information-theoretic concept of the entropy to identify the best routes in a network by exploiting the uncertainty involved in the selection of the best paths.

 
-• Selected Publications (last 5 years)

N. B. Karayiannis, Y. Xiong, G. Tao, J. D. Frost, Jr., M. S. Wise, R. A. Hrachovy, and E. M. Mizrahi, ``Automated detection of videotaped neonatal seizures of epileptic origin,'' Epilepsia, vo. 47, no. 6, pp. 966-980, 2006.

N. B. Karayiannis, A. Mukherjee, J. R. Glover, P. Y. Ktonas, J. D. Frost Jr., R. A. Hrachovy, and E. M. Mizrahi, "Detection of pseudosinusoidal epileptic seizure segments in the neonatal EEG by cascading a rule-based algorithm with a neural network," IEEE Transactions on Biomedical Engineering, vol. 53, no. 4, pp. 633-641, 2006.

G. Purushothaman and N. B. Karayiannis, "On the capacity of feed-forward neural networks for fuzzy classification,'' Journal of Applied Functional Analysis, vol. 1, no. 1, pp. 9-32, 2006

N. B. Karayiannis and G. Tao, "An improved procedure for the extraction of temporal motion strength signals from video recordings of neonatal seizures," Image and Vision Computing, vol. 24, no. 1, pp.
27-40, 2006.

N. B. Karayiannis, A. Mukherjee, J. R. Glover, J. D. Frost, Jr., R. A. Hrachovy, and E. M. Mizrahi, ``An evaluation of quantum neural networks in the detection of epileptic seizures in the neonatal electroencephalogram," Soft Computing Journal, vol. 10, no. 4, pp. 382-396, 2006.

N. B. Karayiannis and S. Nadella, ``Power-conserving routing of ad hoc mobile wireless networks based on entropy-constrained algorithms,'' AdHoc Networks Journal, vol. 4, no. 1, pp. 24--35, 2006.

N. B. Karayiannis and J. Chookiarti, "Regularized adaptive detectors for code-division multiple-access signals," IEEE Transactions on Wireless Communications, vol. 4, no. 4, pp. 1749-1758, 2005.

N. B. Karayiannis, G. Tao, Y. Xiong, A. Sami, B. Varughese, J. D. Frost, Jr., M. S. Wise, and E. M. Mizrahi, "Computerized motion analysis of videotaped neonatal seizures of epileptic origin," Epilepsia, vol. 46, no. 6, pp. 901-917, 2005.

N. B. Karayiannis, B. Varughese, G. Tao, J. D. Frost Jr., M. S. Wise, and E. M. Mizrahi, "Quantifying motion in video recordings of neonatal seizures by regularized optical flow methods," IEEE Transactions on Image Processing, vol. 14, no. 7, pp. 890-903, 2005.

N. B. Karayiannis, Y. Xiong, J. D. Frost, Jr., M. S. Wise, and E. M. Mizrahi, "Quantifying motion in video recordings of neonatal seizures by robust motion trackers based on block motion models," IEEE Transactions on Biomedical Engineering, vol. 52, no. 6, pp. 1065-1077, 2005.

N. B. Karayiannis, A. Sami, J. D. Frost, Jr., M. S. Wise, and E. M. Mizrahi, ``Automated extraction of temporal motor activity signals from video recordings of neonatal seizures based on adaptive block matching,'' IEEE Transactions on Biomedical Engineering, vol. 52, no. 4, pp. 676--686, 2005.

N. B. Karayiannis and J. Chookiarti, "Directly estimated adaptive detectors for code-division multiple access signals," IEEE Transactions on Communications, vol. 53, no. 2, pp. 356-365, 2005.

N. B. Karayiannis and M. M. Randolph-Gips, "Soft learning vector quantization and clustering algorithms based on non-Euclidean norms: Single-norm algorithms," IEEE Transactions on Neural Networks, vol. 16, no. 2, pp. 423-435, 2005.

N. B. Karayiannis and J. Chookiarti, "Indirectly estimated adaptive detectors for code-division multiple-access signals," IEEE Transactions on Signal Processing, vol. 52, no. 10, pp. 2677-2689, 2004.

N. B. Karayiannis and M. M.Randolph-Gips, "Non-Euclidean c-means clustering algorithms," Intelligent Data Analysis-An International Journal, vol. 7, no. 5, pp. 405-425, 2003.

Nicolaos B. Karayiannis and Mary M. Randolph-Gips, "On the Construction and Training of Reformulated Radial Basis Function Neural Networks," IEEE Transactions on Neural Networks, vol. 14, no. 4, pp. 835-846, 2003.

N. B. Karayiannis and M. M. Randolph-Gips, "Soft Learning Vector Quantization and Clustering Algorithms Based on Non-Euclidean Norms: Multinorm Algorithms," IEEE Transactions on Neural Networks, vol. 14, no. 1, pp. 89-102, 2003.

N. B. Karayiannis, "Advancing Videometry Through Applications: Quantification of Neonatal Seizures From Video Recordings," Proceedings of Fourteenth International Conference on Digital Signal Processing, Santorini, Greece, July 1-3, 2002, in press (invited paper).

N. B. Karayiannis, "Soft learning vector qantization and clustering algorithms based on mean-type aggregation operators," International Journal of Fuzzy Systems, vol. 4, no. 3, pp. 739-751, 2002.

N. B. Karayiannis, R. Kretzschmar, and H. Richner, "Pattern classification based on quantum neural networks: A case study," in Pattern Recognition: From Classical to Modern Approaches, S. K. Pal and A. Pal, (Eds.), World Scientific Publishing, Singapore, pp. 301-328, 2001.

N. B. Karayiannis, "Integrating the development of supervised and unsupervised neural network models: Why and how," Proceedings of Fourth International Conference on Neural Networks and Expert Systems in Medicine and Health Care, Milos Island, Greece, June 20-22, 2001, pp. 11-20 (invited paper).

N. B. Karayiannis, S. Srinivasan, R. Bhattacharya, M. S. Wise, J. D. Frost, Jr., and E. M. Mizrahi, "Extraction of motion strength and motor activity signals from video recordings of neonatal seizures," IEEE Transactions on Medical Imaging, vol. 20, no. 9, pp. 965-980, 2001.

N. B. Karayiannis and Y. Li, "A replenishment technique for low bit-rate video compression based on wavelets and vector quantization," IEEE Transactions on Circuits and Systems for Video Technology, vol. 11, no. 5, pp. 658-663, 2001.

N. B. Karayiannis, "Soft learning vector quantization and clustering based on reformulation," in Nonlinear Biomedical Signal Processing, vol. I, M. Akay, (Ed.), IEEE Press, pp. 158-197, 2000.

N. B. Karayiannis, "An axiomatic approach to reformulating radial basis neural networks," in Nonlinear Biomedical Signal Processing, vol. I, M. Akay, (Ed.), IEEE Press, pp. 122-157, 2000.

N. B. Karayiannis and S. Behnke, "New radial basis neural networks and their application in a large-scale handwritten digit recognition problem," in Recent Advances in Artificial Neural Networks: Design and Applications, L. C. Jain and A. M. Fanelli, (Eds.), CRC Press, Boca Raton, FL, pp. 39-94, 2000.

N. B. Karayiannis and Z. Liu, "Split and merge codebook design algorithms for image compression," Journal of Electronic Imaging, vol. 9, no. 4, pp. 509-520, 2000.

N. B. Karayiannis and T. C. Wang, "Compression of digital mammograms using wavelets and fuzzy algorithms for learning vector quantization," in Soft Computing for Image Processing, S. K. Pal, A. Ghosh and M. K. Kundu, (Eds.), Physica-Verlag, Heidelberg, pp. 205-245, 2000.

N. B. Karayiannis and N. Zervos, "Entropy-constrained learning vector quantization algorithms and their application in image compression," Journal of Electronic Imaging, vol. 9, no. 4, pp. 495-508, 2000.

N. B. Karayiannis, "Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators," IEEE Transactions on Neural Networks, vol. 11, no. 5, pp. 1093-1105, 2000.

N. B. Karayiannis, "Generalized fuzzy c-means algorithms," Journal of Intelligent & Fuzzy Systems, vol. 8, no. 1, pp. 63-81, 2000.

N. B. Karayiannis}, "From aggregation operators to soft learning vector quantization and clustering algorithms," in Kohonen Maps, E. Oja and S. Kaski (Eds.), Elsevier Publishers, Amsterdam, pp. 47-56, 1999 (invited paper).

N. B. Karayiannis and P.-I Pai, "A family of fuzzy algorithms for learning vector quantization," International Journal of Engineering Intelligent Systems, vol. 7, no. 3, pp. 145-156, 1999.

N. B. Karayiannis, "An axiomatic approach to soft learning vector quantization and clustering," IEEE Transactions on Neural Networks, vol. 10, no. 5, pp. 1153-1165, 1999.

N. B. Karayiannis, "Reformulated radial basis neural networks trained by gradient descent," IEEE Transactions on Neural Networks, vol. 10, no. 3, pp. 657-671, 1999.

N. B. Karayiannis and P.-I Pai, "Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization," IEEE Transactions on Medical Imaging, vol. 18, no. 2, pp. 172-180, 1999.

N. B. Karayiannis, "Reformulating learning vector quantization and radial basis neural networks," Fundamenta Informaticae, vol. 37, pp. 137-175, 1999.

T. C. Wang and N. B. Karayiannis, "Detection of microcalcifications in digital mammograms using wavelets," IEEE Transactions on Medical Imaging, vol. 17, no. 4, 498-509, 1998.

S. Behnke and N. B. Karayiannis, "Competitive neural tress for pattern classification," IEEE Transactions on Neural Networks, vol. 9, no. 6, pp. 1352-1369, 1998.

G. Purushothaman and N. B. Karayiannis, "Feed-forward neural architectures for membership estimation and fuzzy classification," International Journal of Smart Engineering System Design, vol. 1, pp. 163-185, 1998.

N. B. Karayiannis, P.-I Pai, and N. Zervos, "Image compression based on fuzzy algorithms for learning vector quantization and wavelet image decomposition," IEEE Transactions on Image Processing, vol. 7, no. 8, pp. 1223-1230, 1998.

N. B. Karayiannis, "Learning vector quantization: A review," International Journal of Smart Engineering System Design, vol. 1, pp. 33-58, 1997.

N. B. Karayiannis and W. Mi, "Growing radial basis neural networks: Merging supervised and unsupervised learning with network growth techniques," IEEE Transactions on Neural Networks, vol. 8, no. 6, pp. 1492-1506, 1997.

N. B. Karayiannis and J. C. Bezdek, "An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering," IEEE Transactions on Fuzzy Systems, vol. 5, no. 4, pp. 622-628, 1997.

N. B. Karayiannis, "Fuzzy partition entropies and entropy constrained clustering algorithms," Journal of Intelligent & Fuzzy Systems, vol. 5, no. 2, pp. 103-111, 1997.

G. Purushothaman and N. B. Karayiannis, "Quantum neural networks (QNNs): Inherently fuzzy feed-forward neural networks," IEEE Transactions on Neural Networks, vol. 8, no. 3, pp. 679-693, 1997.

N. B. Karayiannis, "A methodology for constructing fuzzy algorithms for learning vector quantization," IEEE Transactions on Neural Networks, vol. 8, no. 3, pp. 505-518, 1997.