The Knowledge Engineering and Discovery Research Institute

KEDRI

(www.kedri.info)

Highlights of Five Years Research and Postgraduate Teaching

2002 - 2007

Funded by Auckland University of Technology (AUT)

and the New Economy Research Fund – Foundation of Research Science and Technology (FRST)

KEDRI: Five years of knowledge engineering and discovery research

Professor Nikola Kasabov, FRSNZ, FNZCS, Founding Director and Chief Scientist

KEDRI - the Knowledge Engineering and Discovery Research Institute of Auckland University of Technology was established in June 2002 and since then has been developing novel information processing methods, technologies and their applications to enhance discoveries across different areas of science and engineering. The methods are mainly based on principles from Nature, such as brain information processing, evolution, genetics, quantum physics.

KEDRI research team includes 6 senior research fellows, 20 PhD and Masters students, 6 associate senior researchers. Three of our PhD students have been awarded Top Achiever Doctoral (TAD) Awards by the Tertiary Education Commission. KEDRI reports to the AUT PVC Research. Administratively it is allocated in the Faculty of Design and Creative Technologies. Along with the internal funding from AUT, we have received more than $3.8 mln. external funding from the New Economy Research Fund – NERF/FRST, from research and commercial partners - Fonterra, Telecom, Middlemore hospital, PEBL, Intuto, ViaLactia BS, the SCOPE project, the CORE Bioprotection, and others. KEDRI researchers have published 2 monograph books, 60 papers in top professional journals (such as IEEE Transactions, Neural Networks, Neurocomputing, Pattern Recognition, AI in Medicine, Springer LNCS), 70 papers in international conference proceedings, 15 book chapters and 2 PCT patents. In the 2006 NZ PBRF review, KEDRI achieved an average score of 7, and ranks among the top in the subject area. KEDRI relies on a strong collaboration with NZ academic and commercial partners, and international partners from 12 countries. KEDRI’s international reputation was enhanced by hosting 4 international conferences on Neuro-Computing and Evolving Intelligence (NCEI), 3 international summer schools on Bioinformatics. KEDRI is going to be the host of the premier Asia-Pacific Neural Network Assembly Conference ICONIP’08 (26-28.11.2008). KEDRI has 5 research centres and one laboratory that reflect the projects undertaken: (1) Neurocomputing and Computational Intelligence; (2) Neuroinformatics and Brain Study; (3) Bioinformatics; (4) Data Mining and Decision Support Systems; (5) Adaptive Pattern Recognition Systems; (6) English and Maori translation systems. The 5th Anniversary of KEDRI is an opportunity to acknowledge the researchers and the achievements of the Institute, to reflect critically on our work, and to look forward to new horizons and new challenges. I would like to acknowledge the tremendous support we have received from the VC and the DVC of AUT, from the Research Office and the AUT Technology Park, from the Faculty of Design and Creative Technologies and from the School of Computing and Mathematical Sciences, from NERF/FRST and from our research partners in NZ and overseas. Thank you all!

The Opening of KEDRI in June 2002

(From left: Prof. P.Sallis - DVC, Prof. S.MacDonell, Prof. N.Kasabov, Prof. D.Graydon – PVC and Dean Faculty of Business, Derek McCormack – VC AUT)

…and the people of KEDRI now, 2007

Part of the KEDRI team. From left: Peter Hwang (PhD), Raphael Hu (PhD), Alex Tjahjana (PhD), Simei Wysoski (TAD PhD), Joyce D’Mello, Dr Shaoning Pang, Anju Verma (TIF PhD), Dr. Ilkka .Havukkala, Dr. Qun Song, Prof. Nikola Kasabov, Scott Heappey (Masters student), Maggie Ma (TAD PhD), Dr.Lubica.Benuskova, Vishal Jain (PhD), Dr. Michael Defoin-Platel (for other KEDRI members, see www.kedri.info)

The people at KEDRI

Profesor Nikola Kasabov, FRSNZ, FNZCS Founding Director and Chief Scientist Prof. Kasabov has published more than 400 publications, including: 112 journal papers, 12 monograph books, 45 book chapters and 27 patents. He is recipient of the RSNZ Medal for Science and Technology; Vice President of the INNS ; Past President and President-elect of APNNA; Assoc. Editor of Neural Networks, IEEE Tr. NN and other int. journals. Previously, he was with the University of Otago (1992-2002), University of Essex (UK) and TU Sofia.

KEDRI Asst. Manager and PA to Prof. Kasabov: Mrs Joyce D’Mello (jdmello@aut.ac.nz)

Senior Research Fellows and Centre Directors:

Dr. Qun Song Expertise: neuro-fuzzy systems. Publications in top journals, incl. Neural Networks, IEEE Trans. FS, AI in Medicine. Recipient of KEDRI Annual Awards. Dr.Lubica Benuskova Expertise: cognitive neuroscience, bio-physics, neural networks. Publications in top journals, incl. PNAS, NN, IJNS. Dr. Paul Pang Expertise: pattern recognition, support vector machines, on-line learning. Publications in top journals incl. IEEE Trans. SMC

Researchers: Prof. Stephen MacDonell Dr Michael Defoin-Platel Dr. Ilkka Havukkala Assoc. Prof. Frances Joseph Dr Mark Laws (associate) Richard Walton (associate) Dr Zeke Chan (associate) Dr. Russel Pears (associate) A/Prof. Brett Collins (associate) Dougal Greer (2003-2005)

Distinguished Scientist Awards: Prof. T.Yamakawa, KIT, Japan; Prof. M. Arbib, USC, USA; Prof. W. Freeman, UC Berkeley; Prof. D.Yun, U.Hawaii, USA; Prof. M. Fedrizzi, U.Trento, Italy Collaborators: Australia: Prof. T.Gedeon, ANU Germany: Prof. A.Koenig, U. Kaiserslautern Hungary: Prof. L. Koczy, BTU Italy: Prof. M.Fedrizzi, U.Trento Japan: Prof. M.Cassim, Ritsumeikan; Prof. H. Kojima, Tamagawa U.; Dr. Cees van Leeuwen, RIKEN; A/P Seiichi Ozawa, Kobe U; Prof. M.Tsukada, Tamagawa U.; Prof. T.Yamakawa, KIT Korea: Prof. S.Yang Bang, POSTECH; Prof. Sung-bae Cho,Yon Sei U.; Prof. Soo-Young Lee, KAIST The Netherlands: Prof. Jaap van den Herik, U. Maastricht; Prof. Anton Nijholt, U. Twente Singapore: A/P Jagath C Rajapakse, NTU Spain: Prof. Richard Duro, U. Da Coruna Switzerland: Prof. A.Villa, U. Lausanne UK: Dr. Plamen Angelov, U. Lancaster; Prof. M.McGinnity, U. Ulster; Dr. Vasile Palade, U. Oxford USA: Dr. V. Brusic, Harvard; Dr. D.Dimitrov, NIH; Dr. Masoud Nikravesh, U. Berkeley NZ: Steve Cosgrove, Fonterra; Dr. Timothy Hong, GNSL; Prof. A. Rodrigo, U. Auckland; Dr G. Coghill, U. Auckland; A/P R.North, U. Auckland; Prof. M.Paulin, U. Otago; Dr. Mike Sullivan, U. Otago; Dr. Sue Worner, Lincoln U.; Dr. L. Huang, Massey University; Dr. Mark Marshall, Middlemore Hospital

Postgraduate students completed or in the process of completion:

David Parry (PhD)

Subana Shanmuganathan (PhD)

David Zhang (PhD, funded by NERF)

A.Ghobakhlou (PhD funded by NERF)

Raphael Hu (Masters)

Nisha Mohan (Masters)

Andreas Magusin (Masters)

Lawrence Wang (Masters)

Current PhD students: Vishal Jain, (funded by NERF) Anju Verma, (funded by TIF) Boris Bacic, (AUT) Stefan Schliebs (funded by NERF) Snjezana Soltic, (MIT lecturer) Peter Hwang (funded by NERF) Raphael Hu (funded by KEDRI) Alex Tjahjana (funded by KEDRI) Harya Widiputra (funded by KEDRI) Current Masters Research Students Peter Wang Aravind Raghavan Rakesh Gudey Kevin Li Tsung-chun Tsai Parag Bhatnagar Karthik Suman Ly Thanh Trung 25 Visiting Researchers and Students visited KEDRI from 13 countries • Australia, China, Germany, • Hungary, Italy, Japan, Korea, • Singapore, Sweden, • The Czech Republic; • The Netherlands, • The United Kingdom, USA ( for details, see www.kedri.info)

Liang Goh The first completed KEDRI PhD student. Funded by NERF. Currently with Duke University, USA Topic: Bioinformatics

Paulo Gottroy PhD student. TAD Award. Topic: Ontology systems

Maggie Ma PhD student. TAD Award. Topic: Medical decision support systems

Simei Wysoski TAD Award. Topic: Spiking neural netwoks for pattern recognition.

Centre for Neurocomputing and

Computational Intelligence

Centre for Neuroinformatics and Brain Study

Centre for Bioinformatics

Centre for Data Mining and

Decision Support Systems

Centre for Adaptive Pattern Recognition

Systems

Laboratory English /Maori translation

Systems

NZ Universities: • University of

Auckland • University of Otago • Lincoln University

and the CoRE for Bioprotection

• Massey University

NZ based research and commercial partners: • FONTERRA • TELECOM, Lucent

and MediaLab • PEBL • CRI- GNS • SCION/CRI-Forest

Research Institute • ViaLactia BS • Biometric

Technologies Ltd • Fidelity Genetics • Middlemore

Hospital • Intuto

International collaboration: • Australia – ANU • Bulgaria - Tech. University

Sofia, Plovdiv • Germany – University of

Kaiserslautern, International University

• Hungary - Budhapest Technical University

• Italy - University of Trento • Japan - Kobe University,

Kyushu Institute of Technology, RIKEN, Ritsumeikan University, Tamagawa University

• Korea - POSTECH, KAIST, Yonsei University

• Netherlands - University of Maastricht, University of Twente

• Singapore - Nanyang Technological University

• Spain – U. da Coruna • Switzerland - University of

Lausanne • UK – University of

Lancaster, Oxford University, University of Ulster

• USA - UC, Berkeley, Harvard University, National Cancer Institute, NIH

KEDRI’s National and International Partners

Projects at KEDRI

2002 - 2007, NERF/FRST, Connectionist-Based Intelligent Information Systems. 2003 - 2007, CORE Bioprotection, Lincoln Univ., - Neural Networks for Decision Support. 2004 - 2008, Univ. of Auckland, Personalised prognosis of pre-eclampsia.

2006, AUT – with School of Arts and Design, Design of a brain-gene ontology. 2006, Fonterra, Predicting milk volume production. 2006, Telecom/Lucent/Medialab, UA and U Canterbury, Closed loop optimisation. 2006, Intuto, Design of a neuro-fuzzy e-learning system. 2004, Fonterra, Evaluation applicability of evolving connectionist systems. 2004, ViaLactia Biosciences, NZ herd phenotype quality analysis. 2004, Middlemore Hospital, Renal function evaluation method and system. 2003, TECH NZ, CVD risk analysis and prediction.

Research Informed Teaching

KEDRI researchers coordinate, teach and contribute to the following Masters papers at the School of Computing and Mathematical Sciences: Data mining and Knowledge Engineering. Bioinformatics. Contemporary Issues of IT.

Research Centres at KEDRI

1. Centre for Neurocomputing and Computational Intelligence Contact person: Prof. Nikola Kasabov, Centre Director, email: nkasabov@aut.ac.nz The Centre develops generic methods for efficient and accurate representation and processing of data, information and knowledge. Some of the developed methods have been used for discoveries in large research projects, e.g. SCOPE – University of Auckland, Bio-protection – Lincoln University, Fonterra and Telecom NZ. Current research topics include: • Neural networks and more specifically: evolving connectionist methods for adaptive learning and knowledge discovery; neuro-fuzzy models. • Spiking neural networks – methods and applications (Fig.1) • Methods for personalised modelling (Fig. 2) • Evolutionary computation • Evolving Ontologies (Fig. 2) • Quantum inspired methods and systems (Fig. 3) • Methods for incremental and on-line learning

(a) (b) Figure 1 (a) Left: Representation of biological neuron; Right: Basic spiking neuron unit; b) The KEDRI spiking neural network architecture for visual pattern recognition.

Figure 2. The KEDRI methodology and platform for ontology-based personalized decision support systems consists of two interconnected parts: (1) An ontology/database sub-system; (2) Machine learning sub-system.

Figure 3. The KEDRI quantum inspired evolutionary algorithm performs exponentially faster and more accurately than the classical algorithms when evaluating combinations of variables for a modelling task. Selected publications:

1. Kasabov, N., Brain-, gene-, and quantum inspired computational intelligence: Challenges and

opportunities, in: B.Reusch (ed) Computational Intelligence, Theory and Practice, Advances in Soft Computing, Springer, 521-544, 2006

2. 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

3. Qun Song, Tian Min Ma and Nikola Kasabov, TTLSC – Transductive Total Least Square Model for Classification and Its Application in Medicine, Advanced Data Mining and Applications, Lecture Notes in Computer Science, Volume 4093, Pages 197-204, 2006

4. Chan S.H., Kasabov N., Fast Neural Network Ensemble Learning via Negative-Correlation Data Correction, IEEE Transaction on Neural Networks 2005, Vol. 16, Issue 6, pp 1707-1710

5. Pang, S., S. Ozawa and N. Kasabov, Incremental Linear Discriminant Analysis for Classification of Data Streams, IEEE Trans. SMC-B, vol. 35, No. 5, 2005, 905 – 914

6. Song Q. and N. Kasabov, NFI: A Neuro-Fuzzy Inference Method for Transductive Reasoning, IEEE Transactions on Fuzzy Systems, Volume 13, Issue 6, pp 799-808, 2005

7. Pang, S. , Seiichi Ozawa, Nikola Kasabov, Chunk Incremental LDA Computing on Data Streams, Lecture Notes in Computer Science, Volume 3497, Jan 2005, pp.51-56

8. Song Q. , and N. Kasabov, TWRBF – transductive RBF Neural Network with Weighted Data Normalization, Lecture Notes in Computer Science, Vol.3316, Springer Verlag, 2004, 633-640

9. Chan Z.and N.Kasabov, Evolutionary computation for on-line and off-line parameter tuning of evolving fuzzy neural networks, Int. J. of Computational Intelligence and Applications, Imperial College Press, vol. 4, N.3, September 2004, 309-319

10. S.Wysoski, L.Benuskova, and N. Kasabov (2007) Fast and Adaptive Network of Spiking Neurons for Multi-view Visual Pattern Recognition, Neurocomputing, in print

11. M.Defoin-Platel, S.Schliebs, N.Kasabov (2007) A versatile quantum inspired evolutionary algorithm, Proc. IEEE Congress on Evolutionary Computation.

12. Defoin-Platel, M., Schliebs, S. and N.Kasabov, Quantum inspired feature selection and neural network models for time series prediction, IJCNN, NN3 competition, 2007

2. Centre for Neuroinformatics and Brain Study

Contact person: Dr. Lubica Benuskova, Centre Director, email: lbenusko@aut.ac.nz The Centre develops brain-like computational methods and systems for learning and knowledge discovery. The methods are applicable in the areas of neuroinformatics and neuroscience, as well as for solving complex problems of Artificial Intelligence, such as multimodal information processing. Current research topics include: • Modelling learning and memory mechanisms in the brain. • Spiking neural networks: methods, systems, implementations, applications. • Brain data analysis (EEG, fMRI). • Computational neuro-genetic modelling (CNGM): integrating gene and brain data to model brain functions (Fig. 4). • The world-first Brain-Gene–Simulation Ontology (BGO): A repository of conceptual and factual data, information, knowledge and models related to brain structures, functions, diseases and the genes/proteins involved in them. This is used for teaching and research. Figure 4. The world-first dynamic computational neuro-genetic model (CNGM) developed at KEDRI consists of gene regulatory network to model gene interactions within a spiking neural network model. The model is optimised so, that the model behaviour matches real brain data. Selected publications: 1. Benuskova L, Kasabov N, Modeling L-LTP based on changes in concentration of pCREB transcription factor, Neurocomputing, in print, MS Num D-06-00565 2. Kasabov N. and L. Benuskova, Computational Neurogenetics, International Journal of Theoretical and Computational Nanoscience, Vol. 1 (1) American Scientific Publisher, 2004, 47-61 3. Benuskova L, Jain V, Wysoski SG and Kasabov N, Computational neurogenetic modeling: a pathway to new discoveries in genetic neuroscience. Intl. Journal of Neural Systems, 16(3): 215-227, 2006

3. Centre for Bioinformatics

Contact person: Prof. Nikola Kasabov, Acting Centre Director, email: nkasabov@aut.ac.nz The Centre develops specific information processing methods and systems applicable to problems in Bioinformatics and Medical Decision Support. Current research includes: • Computational modelling of gene/protein expression data and gene regulatory networks related

to diagnosis and prognosis of disease and drug marker discovery • Software system for gene expression analysis - SIFTWARE (Fig. 5) • Software for gene regulatory network modelling • Integrated systems for biological data analysis and modelling • Nutrigenomic decision support systems for personalised advice • Pest risk modelling and evaluation (with the CORE for Bioprotection, Lincoln University)

Figure 5. A snapshot of the patented Gene Profiling Software SIFTWARE developed with Pacific Edge Biotechnology Ltd (www.peblnz.com).

Selected publications: 1. Kasabov, N., L.Goh and Mike Sullivan, Integrated Prognostic Profiles: Combining Clinical and Gene Expression Information through Evolving Connectionist Approach, Chapt.10, in: Bajic. V, Tan Tin Wee (eds), Inform. Proc. and Living Systems, Imperial College Press, Singapore, 2005, 695-706 2. Pang, Shaoning, Ilkka Havukkala, Nikola Kasabov, Two-Class SVM Trees (2-SVMT) for Biomarker Data Analysis, Lecture Notes in Computer Science, Volume 3973/2006, pp 629-634 3. Chan, Z., N.Kasabov, Lesley Collins, A Two-Stage Methodology for Gene Regulatory Network Extraction from Time-Course Gene Expression Data, Expert Systems with Applications: An International Journal, Volume 30, Issue 1, January 2006, Pages 59-63

4. Centre for Data Mining and Decision Support Systems Contact person: Dr. Qun Song, Centre Director, email: qsong@aut.ac.nz The Centre develops software and hardware systems to enable comprehensive data analysis, knowledge discovery and decision support across a range of domain areas. Current research topics include: • NeuCom (www.theneucom.com) - a self-programmable, learning and reasoning computer

environment (Fig. 6). NeuCom is currently being used by 35 universities from all over the world for teaching and research.

• On-line prediction and resource optimisation of mobile phone calls traffic (with Telecom/Lucent/MediLab, U Auckland and U Canterbury) (Fig. 6).

• On-line prediction and optimisation of resources for milk delivery and production (with Fonterra) (Fig. 6).

• Medical decision support systems. Personalised models for renal function evaluation (with Middelmore Hospital)

Figure 6. A snapshot of the data mining and decision support environment NeuCom (www.theneucom.com) and two of its applications with Telecom and Fonterra.

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5. Centre for Adaptive Pattern Recognition Systems Contact person: Dr. Paul Pang, Acting Centre Director, email: spang@aut.ac.nz The Centre develops novel methods for signal processing and modelling using combination of different modalities - speech, image, video, motion, and sensory information. Current research projects include:

• Speech recognition • Image and video processing • Odour recognition (“artificial nose”) • Adaptive modelling of human motion and application in sport couching • Integrated multimodal systems (speech and image) (Fig. 7) • Biometric applications • Adaptive mobile robots (Fig.8)

Figure 7. An integrated environment for person identification system development, based on image and speech information, was patented as a PCT.

                                             Figure 8. The robotic soccer system developed by L.Huang utilised the KEDRI on-line learning method ECF and won a gold medal at the World ROBOCUP 2004 in Seoul.

Selected publications: 1. Pang, Shaoning, Nikola Kasabov, Investigating LLE Eigenface on Pose and Face Identification, Lecture Notes in Computer Science, Volume 3972/2006 pp 134-139 2. Ozawa, S., Shaoning Pang and Nikola Kasabov, Incremental learning of feature space and classifier for on-line pattern recognition, International Journal of Knowledge based and Intelligent Engineering Systems, Volume 10, 2006, pp 57-65 3. Ghobakhlou, A., D. Zhang and N. Kasabov An Evolving Neural Network Model for Person Verification Combining Speech and Image, Lecture Notes of Computer Science, vol. 3316, Springer, 2004, 381-386 4. N. Kasabov, A. Ghobakhlou, Adaptive Sound and Image Learning System and Method, PCT WO 2005/038774 A1 5. Huang, L., Q.Song and N.Kasabov, Evolving connectionist system based role allocation for robotic soccer, Int. J. Advanced Robotic Systems, 2007

6. Laboratory for English and Maori translation systems Contact person: Dr. Mark Laws, Associate Lab. Director, email: maaka@wananga.ac.nz A data base of English, Maori and other Polynesian languages has been developed by Dr Mark Laws over the last 10 years and is made available free at: http://translator.kedri.info/ The Translator has been extensively used for education and research purposes in New Zealand and overseas (fig.9).

Figure 9. A snapshot of the English and Maori on-line word translator system developed by Dr Mark Laws and maintained by KEDRI.

Publications by KEDRI KEDRI researchers have published more than 60 papers in top professional journals such as IEEE Transactions, Neural Networks, Neurocomputing, Pattern Recognition, AI in Medicine, 2 monograph books, 70 refereed conference papers in Springer LNCS and other, 15 book chapters, 2 PCT patent submissions. Monograph books Kasabov, N. (2007) Evolving Connectionist

Systems: The Knowledge Engineering Approach, Springer, London (www.springer.de)

Benuskova, L and Kasabov, N. (2007) Computational Neurogenetic Modelling, Springer, N.Y.

Other selected publications Kasabov, N., Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and

Opportunities, in: W.Duch and J.Manzduk (eds) Challenges in Computational Intelligence, Springer, 2007

Kasabov, N., Global, local and personalised modelling and profile discovery in Bioinformatics: An integrated approach, Pattern Recognition Letters, 2007 28(6):673-685

Chan, Zeke S.H., Lesley Collins and N. Kasabov Bayesian learning of sparse gene regulatory networks, Biosystems, Volume 87, Issues 2-3, February 2007, Pages 299-306

Benuskova L, Jain V, Wysoski SG and Kasabov N., Computational neurogenetic modeling: a pathway to new discoveries in genetic neuroscience. Intl. Journal of Neural Systems, 16(3): 215-227, 2006

Song, Q. and Kasabov, N. TWNFI- a transductive neuro-fuzzy inference system with weighted data normalisation for personalised modelling, Neural Networks, 2006 19(10): 1591-1596

Song, Q., N. Kasabov, T. Ma, M. Marshall, Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: a case study on renal function evaluation, Artificial Intelligence in Medicine, February, 2006

Gottgtroy P., Kasabov N., Macdonell S., Evolving Ontologies for Intelligent Decision Support, Elsevier, Fuzzy Logic And The Semantic Web, Chapter 21, pp 415-439, 2006

Havukkala I, Pang S, Jain V, Kasabov N, Classifying MicroRNAs by Gabor Filter Features from 2D Structure Bitmap Images on a Case Study of Human microRNAs, Journal of Theoretical and Computational Nanoscience, Volume 2, No. 4, pp 506-513, 2005

Marshall, M.R. , Q. Song, T.M. Ma, S. MacDonell, N.Kasabov, Evolving Connectionist System versus Algebraic Formulae for Prediction of Renal Function from Serum Creatinine, Kidney International, vol. 67 (2005), pp. 1944 – 1954

Ozawa, S., S.Too, S.Abe, S. Pang and N. Kasabov, Incremental Learning of Feature Space and Classifier for Online Face Recognition, Neural Networks, August, 2005, pp 575-584

Pang, S., S. Ozawa and N. Kasabov, Incremental Linear Discriminant Analysis for Classification of Data Streams, IEEE Trans. SMC-B, vol. 35, No. 5, 2005, 905 – 914

Soltic, S., S.Pang, N.Kasabov, S. Worner and L.Peacock, Dynamic Neuro-fuzzy Inference and Statistical Models for Risk Analysis of Pest Insect Establishment, Lecture Notes of Computer Science, vol. 3316, Springer, 2004, 971-976.

The KEDRI Computational Intelligence Software Repository, 2007 The KEDRI CI Repository contains more than 100 traditional and original methods, software systems and publications for intelligent data analysis, modelling and knowledge discovery, including:

- Generic CI Methods and Systems; - CI for Neuroinformatics and Brain Study; - CI for Bioinformatics and Medical Applications; - CI for Data Mining and Decision Support Systems; - CI for Speech, Image and Signal Processing

The KEDRI CI Repository is accessible at http://www.kedri.info or obtained as a CD from the Manager. All methods and systems are free to use for education and research.

Conferences organised by KEDRI

KEDRI has hosted 4 international conferences on Neuro Computing and Evolving Intelligence (NCEI), 3 international Summer Schools on Bioinformatics, and is the host of the upcoming Asia-Pacific Neural Network Assembly (APNNA) Conference - ICONIP’2008 (26-28.11.2008).

Some of the participants at the joint NCEI’06 (Neuro- Computing and Evolving Intelligence) and HIS’06 (Hybrid Intelligent Systems) conference, held at the AUT Technology Park and hosted by KEDRI, December 2006. The conference attracted more than 100 participants from 21 countries.