Никола Касабов

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Никола Касабов
български математик
Роден
12 август 1948 г. (69 г.)
Научна дейност
Област Математика, информатика

Проф. Никола Касабов е известен български математик и информатик.

Известен е със своите изследвания по размити системи, невронни мрежи, интелигентни системи, биоинформатика, невроинформатика, изкуствен интелект и др. Преподавател е в Техническия университет на Окланд (Auckland University of Technology) в Нова Зеландия.

Биография[редактиране | редактиране на кода]

Никола Кирилов Касабов е роден на 12 август 1948 г. в град Свищов. Израства и завършва СОУ „Бачо Киро“ в Павликени.

През 1971 г. завършва специалност „Изчислителна техника“ във Висш машинно-електротехнически институт (ВМЕИ, днес Технически университет) в София. След това специализира „Приложна математика“ в същия институт и през 1975 г. защитава докторска степен по математика. До 1989 г. преподава във ВМЕИ - София.

След това работи като преподавател и професор в Университета на Есекс (University of Essex) в Колчестър, Великобритания (1989-1991), Университета на Отаго (University of Otago) в Дънидин, Нова Зеландия (1992-2002) и от 2002 г. - в Техническия университет на Окланд. Гост-професор в университетите: ETH Zurich, Trento (Италия), Shanghai JiaoTong (Китай), TU Kaiserslautern (Германия).

Има публикувани над 600 труда и 3 монографии в областите: невронни мрежи, ИИ, биоинформатика, невроинформатика, анализ на данни, информационно моделиране, извличане на знания от данни. Известни негови теории са: Neuro-fuzzy systems; Evolving connectionist systems; NeuCube spiking neural network; Personalised modelling.

Почетен член (fellow) е на IEEE (Institute for Electrical and Electronic Engineering (2010), член (академик) на Академията на науките на Нова Зеландия (Roayl Society of New Zealand, RSNZ), EU Marie Curie Fellow (2011-2012), почетен гостуващ член на Кралската инженерна академия на Великобритания (Roayl Academy of Engineering, UK). Президент е на Международната асоциация по невронни мрежи (INNS) (2009-2010) и на Асоциацията по невронни мрежи на Азия и Пацифика (APNNA) (1998 и 2008) и текущ член на техните управителни съвети.

Почетен председател на международни конференции, като: ANNES (1993-2001, Otago, New Zealand), NCEI (2002-2015, Auckland); ICAN 2013 (ТУ София, 2013); EANN 2014 (ТУ София 2014). Повече информация за проф. Никола Кирилов Касабов може да се намери на http://www.kedri.aut.ac.nz/.

Носител на множество международни награди, като: APPNA Outstanding Achievement Award (2012); INNS Gabor Award (2012); Bayer Innovator of the Year Award (2007); RSNZ Silver Medal for Science and Technology (2002).

Почетен гражданин е на Павликени от 1989 г. Учредител и спонсор на 2 награди за изключителни постижения на ученици от СУ 'Бачо Киро' в Павликени. Писателката Капка Касабова е негова дъщеря.

Избрани публикации[редактиране | редактиране на кода]

Избрани авторски книги
  • Kasabov, N. Evolving Connectionist Systems: The Knowledge Engineering Approach,Springer Verlag, London, (2007) 458p
  • Benuskova, L. and N.Kasabov, Computational neuro-genetic modelling: Integrating bioinformatics and brain science data, information and knowledge via computational intelligence, Springer, New York, 2007, 290 pages
  • Kasabov, N. Evolving connectionist systems: Methods and applications in bioinformatics, brain study and intelligent machines, Springer Verlag, London, (2003) 308p
  • Kasabov, N. Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering. Cambridge, Massachussets, MIT Press (1996) 550p
  • Kasabov, N. and Romanski, R. Computer Architectures and Techniques Sofia, Technika (1992) 435p (in Bulgarian)
  • Stoichev, S. and Kasabov, N. Programming in PASCAL. Sofia, Technika (1989) 136p (на Български)
  • Stoichev, S. and Kasabov, N. Synthesis and Analysis of Algorithms. Sofia, Technika (1988) 84p (на Български)
  • Stoichev, S. and Kasabov, N. Computer Architectures and Techniques. Sofia, Technika (1986) 348p (на Български)
  • Stoichev, S. and Kasabov, N. Computers - Theory and Practice (Programming of Microprocessors). Sofia, Technika (1984) 120p (на Български)
Избрани редактирани книги
  • N.Kasabov, The Springer Handbook of Bio- and Neuroinformatics, Springer (2014) 1230 p
  • P.Koprinkova, V.Mladenov, N.Kasabov, Neural Networks, Springer,2014.
  • P.Angelov, D.Filev, and N.Kasabov, Evolving intelligent systems, IEEE Press and Wiley, 2010
  • N.Kasabov, Future Directions for Intelligent Systems and Information Sciences, Heidelberg, Physica-Verlag (Springer Verlag) (2000), 420pp
  • N. Kasabov, Kozma, R. Neuro-Fuzzy Techniques for Intelligent Information Systems, Heidelberg, Physica-Verlag (Springer Verlag) (1999), 450pp
  • S.Amari, Kasabov, N. Brain-like Computing and Intelligent Information Systems, Singapore, Springer Verlag (1998), 533 p.
  • M.Koeppen, N.Kasabov and G.Coghill, Advancements in Neural Information Processing, Springer LNCS, vol. 5506/5507, 2009
В международни списания
  • Кasabov, N., E.Capecci, Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes, Information Sciences, DOI: 10.1016/j.ins.2014.06.028, 2014..
  • Kasabov, N. Evolving Connectionist Systems for Adaptive Learning and Knowledge Discovery: The Past, The Present and the Future, Journal of Policy Science, vol. 8, 1-11, Ritsumeikan University Press, Japan, 2014.
  • Kasabov, N. NeuCube: A Spiking Neural Network Architecture for Mapping, Learning and Understanding of Spatio-Temporal Brain Data, Neural Networks vol.52 (2014), pp. 62-76, http://dx.doi.org/10.1016/j.neunet.2014.01.006
  • Kasabov, N., Liang, L., Krishnamurthi, R., Feigin, V., Othman, M., Hou, Z.,. Parmar, P. (2013). Evolving Spiking Neural Networks for Personalised Modelling of Spatio-Temporal Data and Early Prediction of Events: A Case Study on Stroke. Neurocomputing, vol .134, 269-279, 2014, http://dx.doi.org/10.1016/j.neucom.2013.09.049.
  • Pears, R., Widiputra, H., & Kasabov, N. (2013). Evolving integrated multi-model framework for on line multiple time series prediction. Evolving Systems, 4(2), 99-117. doi:10.1007/s12530-012-9069-y, 2013.
  • Liang., Hu., & Kasabov, N. (2013). Evolving Personalized Modeling System for Integrated Feature, Neighborhood and Parameter Optimization utilizing Gravitational Search Algorithm. Evolving Systems. May, 2013, doi:10.1007/s12530-013-9081-x
  • Schliebs, S., & Kasabov, N. (2013). Evolving spiking neural network-a survey. Evolving Systems, 4(2), 87-98, 2013.
  • Kasabov, N., Dhoble, K., Nuntalid, N., & Indiveri, G. (2013). Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition. Neural Networks, 41, 188-201.
  • Pears, R., Widiputra, H. and Kasabov, N., Evolving integrated multi-model framework for on-line multiple time series prediction, Evolving Systems, Springer-Verlag Berlin Heidelberg, DOI: 10.1007/s12530-012-9069-y, 2012.
  • Mohemmed, A. and S.Schliebs and S.Matsuda and N. Kasabov, SPAN: Spike Pattern Association Neuron for Learning Spatio-Temporal Sequences, International Journal of Neural Systems, Vol. 22, No. 4 (2012) 1-16, 2012.
  • Kasabov, N. Evolving, Probabilistic Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition. In INNS Magazine of Natural Intelligence, 1(2): 23-37. Winter 2012
  • Kasabov, N., Schliebs, R., Kojima, H., Probabilistic Computational Neurogenetic Framework: From Modelling Cognitive Systems to Alzheimer’s Disease. IEEE Trans. Autonomous Mental Development, 3(4):300-3011, 2011
  • N. Kasabov, H.N.A. Hamed, Quantum-inspired Particle Swarm Optimisation for Integrated Feature and Parameter Optimisation of Evolving Spiking Neural Networks. International Journal of Artificial Intelligence, Volume 7, Number A11, Page 114-124, 2011. ISSN: 0974-0635, 2011
  • N.Kasabov, To spike or not to spike: A probabilistic spiking neural model, Neural Networks, Vol 23, 1, 2010, 16-19
  • S. Schlebs, M.Defoin-Platel, N.Kasabov, On The Probabilistic Optimization Of Spiking Neural Networks, Int. J. of Neural Systems, Vol. 20, No. 6 (2010) 481–500, World Scientific Publ.Comp.
  • S.Soltic, N.Kasabov, Knowledge extraction from evolving spiking neural networks with a rank order population coding, Int.J.Neural Systems, Vol. 20, No. 6 (2010) 437-445, World Scientific Publ.
  • S.Wysoski, L.Benuskova, N.Kasabov, Evolving Spiking Neural Networks for Audio-Visual Information Processing, Neural Networks, vol 23, issue 7, pp 819-835, September 2010.
  • N.Kasabov, Integrative Connectionist Learning Systems Inspired by Nature: Current Models, Future Trends and Challenges, Natural Computing, Int. Journal, Springer, Vol. 8, Issue 2, pp. 199-218, 2009
  • M. Defoin-Platel, S.Schliebs, N.Kasabov, Quantum-inspired Evolutionary Algorithm: A multi-model EDA, IEEE Trans. Evolutionary Computation, vol.13, No.6, Dec.2009, 1218-1232
  • Schliebs, Michael Defoin Platel, Susan Worner and Nikola Kasabov, Integrated Feature and Parameter Optimization for Evolving Spiking Neural Networks: Exploring Heterogeneous Probabilistic Models, Neural Networks, 22, 623-632, 2009.
  • N.Kasabov, Evolving Intelligence in Humans and Machines: Integrative Connectionist Systems Approach, Feature article, IEEE CIS Magazine, August, 2008, vol.3, Num.3, pp. 23-37
  • N.Kasabov, Adaptive Modelling and Discovery in Bioinformatics: The Evolving Connectionist Approach, International Journal of Intelligent Systems, vol.23 (2008) 545-555
  • Kasabov, N., V.Jain, L.Benuskova, Integrating brain-gene ontology with evolving connectionist system for modelling and knowledge discovery, Neural Networks, 21 (2008), 266-275
  • L.Benuskova and N.Kasabov, Modelling Brain Dynamics Using Computational Neurogenetic Approach, Cognitive Neurodynamics, Springer, vol.2, Num.4, 319-334, December,2008
  • Huang, L., Q.Song and N.Kasabov, Evolving connectionist system based role allocation for robotic soccer, Int. J. Advanced Robotic Systems, Vol. 5, Number 1, March 2008, 59-62
  • N.Kasabov, Global, local and personalised modelling and profile discovery in Bioinformatics: An integrated approach, Pattern Recognition Letters, Vol. 28, Issue 6, April 2007, 673-685
  • N.Kasabov, V. Jain, P. Gottgtroy, L. Benuskova, and F.Joseph, Brain gene ontology and simulation system (BGOS) for a better understanding of the brain. Cybernetics and Systems, June 2007, Vol. 38 (5), pp 495-508, 2007
  • Song, Q. and Kasabov, N. TWNFI- a transductive neuro-fuzzy inference system with weighted data normalisation for personalised modelling, Neural Networks, Vol.19, Issue 10, Dec. 2006, pp. 1591-1596
  • Kasabov, N. Adaptation and Interaction in Dynamical Systems: Modelling and Rule Discovery Through Evolving Connectionist Systems, Applied Soft Computing, 2006, Volume 6, Issue 3, pages 307-322.
  • Kasabov, N., Artificial Neural Networks for Intelligent Information Processing, Transactions of Chemical Engineering, London, June 2001, 27-28.
  • Kasabov, N., and Song, Q., DENFIS: Dynamic Evolving Neural-Fuzzy Inference System and its Application for Time Series Prediction, IEEE Transactions on Fuzzy Systems, Vol. 10, 2, April, (2002) 144-154
  • Kasabov, N. On-line learning, reasoning, rule extraction and aggregation in locally optimised evolving fuzzy neural networks, Neurocomputing, 41 (2001) 25-41
  • Kim, J., A. Mowat, P. Poole, and N. Kasabov, Linear and non-linear pattern recognition models for classification of fruit from visible-near infrared spectra, Chemometrics and intelligent laboratory systems, 51 (2000) 201-216
  • Kasabov, N., Israel, S., and Woodford, B.J., Hybrid evolving connectionist systems for image classification, Journal of Advanced Computational Intelligence, vol.4, 1, (2000) 57-65
  • Kasabov, N., Postma, E. and van den Herik, J. AVIS: a connectionist-based framework for integrated auditory and visual information processing, Information Sciences, vol. 123, (2000) 127-148

Външни препратки[редактиране | редактиране на кода]