Home Page

Reading, after a certain age, diverts the mind too much from its creative pursuits. Any man who read too much and uses his own brain too little falls into lazy habits of thinking.

Albert Einstein

The list of my publications can be also found in the Bournemouth University Research Outputs repository here.

Edited volumes

  • Howlett, R.J., Lovrek, I., Jain, L.C., Lim, C.-P. and Gabrys, B. (Eds) Advances in design and  application of neural networks.  A special edition of Neural Computing and Applications, DOI: 10.1007/s00521-010-0345-0. vol. 1, no. 2, Springer-Verlag. Heidelberg, Germany. February 2010

  • Gabrys, B. and D. Anguita (Eds.). A special issue of the Natural Computing journal on Nature-inspired Learning and Adaptive Systems, 8(2), pp.197-198, Feb 2009.

  • Nguyen N.T., Kolaczek G., Gabrys B. (Eds.) A book entitled "Knowledge Processing and Reasoning for Information Society". ISBN 978-83-60434-38-3, EXIT Publishing House, Warsaw, 2008.

  • Liu, H., R.J. Howlett, B. Gabrys (Eds.). A special issue of the International Journal of Knowledge-based Intelligent Engineering Systems journal, ISNN: 1327-2314, vol.11, no. 4, pp. 199-200, IOS Press, 2007

  • Gabrys, B., R. J. Howlett, L. C. Jain (Eds.)."Knowledge-Based Intelligent Information and Engineering Systems". Proceedings of the 10th International Conference, KES'2006, Part I, II and III, Vol. 4251, 4252 and 4253, Lecture Notes in Artificial Intelligence, Springer-Verlag, 2006.

  • Gabrys, B., K. Leiviska and J. Strackeljan (eds.). A book entitled "Do Smart Adaptive Systems Exist? - Best Practice for Selection and Combination of Intelligent Methods". Published in the Springer series on "Studies in Fuzziness and Soft Computing", vol.173, Springer-Verlag, 2005.

  • Gabrys, B. (ed.). A special issue of the International Journal of Approximate Reasoning entitled Selected Issue on Integration of Methods and Hybrid Systems, vol.35, no. 3, pp. 1-2, 2004. [.pdf]

  • Fyfe, C. and B. Gabrys (eds.). A special issue of the International Journal of Knowledge-based Intelligent Engineering Systems journal entitled Soft Computing & Intelligent Systems for Industry, vol. 6, no. 4, October 2002.

  • Fyfe, C. and B. Gabrys (eds.). A special issue of the Knowledge Based Systems journal, vol. 15, no.1-2, January 2002. [.pdf]

Journal papers and book chapters

  • Kadlec, P. and B. Gabrys, “Local learning-based adaptive soft sensor for catalyst activation prediction”. AIChE Journal. Submitted. Feb 2010.

  • Budka, M., Gabrys, B. and Ravagnan, E., “Robust predictive modelling of water pollution using biomarker data”. Water Research. In press. Mar 2010.

  • Budka, M. and Gabrys, B., “Mixed supervised and unsupervised learning from incomplete data using a physical field model”, Natural Computing. Appeared on-line. DOI: 10.1007/s11047-010-9182-4. In press. Feb 2010.

  • Lemke, C. and B. Gabrys, “Meta-learning for time series forecasting and forecast combination”, Neurocomputing, In press. Nov 2009.

  • Juszczyszyn K., Musial K., Kazienko P.,  and Gabrys B., "Temporal Changes in Local Topology of an Email-based Social Network", Computing and Informatics, In press. 2009.

  • Ruta, D. and B. Gabrys and C. Lemke, “A Generic Multilevel Architecture for Time Series Prediction”, IEEE Transactions on Knowledge and Data Engineering, In press. Dec 2009.

  • Kadlec, P. and B. Gabrys, “Architecture for development of adaptive on-line prediction models”, Memetic Computing, 1 (4), pp. 241-269. Dec. 2009.

  • Kadlec, P., B. Gabrys and S. Strandt, "Data-driven Soft Sensors in the Process Industry", Computers and Chemical Engineering, 33 (4), pp. 795-814, 2009.

  • Riedel, S. and B. Gabrys, "Pooling for Combination of Multi Level Forecasts", IEEE Transactions on Knowledge and Data Engineering, 21 (12), pp. 1753-1766, 2009.

  • Ruta, D. and B. Gabrys, "A Framework for Machine Learning based on Dynamic Physical Fields", Natural Computing, ISSN: 1572-9796 (on-line), 8(2), pp. 219-237, 2009.

  • Kadlec, P. and B. Gabrys, "Gating Artificial Neural Network Based Soft Sensor", A book chapter in New Challenges in Applied Intelligence Technologies, Nguyen, Ngoc Thanh; Katarzyniak, Radoslaw (Eds.) Springer series: Studies in Computational Intelligence, Vol. 134, Springer-Verlag, 2008.

  • Eastwood, M. and B. Gabrys, "Building Combined Classifiers". A book chapter in Knowledge Processing and Reasoning for Information Society. Nguyen N.T., Kolaczek G., Gabrys B. (Eds.) ISBN 978-83-60434-38-3, pp. 139-163, EXIT Publishing House, Warsaw, 2008.

  • Lemke, C. and B. Gabrys, "Forecasting and Forecast Combination in Airline Revenue Management Applications". A book chapter in Knowledge Processing and Reasoning for Information Society. Nguyen N.T., Kolaczek G., Gabrys B. (Eds.) ISBN 978-83-60434-38-3, pp. 231-247, EXIT Publishing House, Warsaw, 2008.

  • Kadlec, P. and B. Gabrys, "Application of Computational Intelligence Techniques to Process Industry Problems". A book chapter in Knowledge Processing and Reasoning for Information Society. Nguyen N.T., Kolaczek G., Gabrys B. (Eds.) ISBN 978-83-60434-38-3, pp. 305-322, EXIT Publishing House, Warsaw, 2008.

  • Eastwood, M. and B. Gabrys, "The Dynamics of Negative Correlation Learning", The special issue of the International Journal of VLSI Signal Processing Systems on "Data Fusion for Medical, Industrial, and Environmental Applications", ISSN: 0922-5773, vol. 49, no. 2, pp. 251-263, November 2007. [.pdf]

  • Riedel, S. and B. Gabrys, "Combination of Multi Level Forecasts" , Paper accepted to the special issue of the International Journal of VLSI Signal Processing Systems on "Data Fusion for Medical, Industrial, and Environmental Applications", ISSN: 0922-5773, vol. 49, no. 2, pp. 265-280, November 2007. [.pdf]

  • Gabrys, B. and D. Ruta, "Genetic Algorithms in Classifier Fusion", Applied Soft Computing, vol. 6, issue 4, pp. 337-347, August 2006. [.pdf]

  • Gabrys, B., "Do Smart Adaptive Systems Exist? - Introduction.", Chapter in the book entitled "Do Smart Adaptive Systems Exist? - Best Practice for Selection and Combination of Intelligent Methods", Springer series on "Studies in Fuzziness and Soft Computing", pp.1-17, Springer-Verlag, 2005.

  • Ruta, D. and B.Gabrys, "Classifier Selection for Majority Voting", Special issue of the journal of INFORMATION FUSION on Diversity in Multiple Classifier Systems, vol. 6, issue 1, pp. 63-81, 1 March 2005. [.pdf]

  • Gabrys, B. and L. Petrakieva, "Combining labelled and unlabelled data in the design of pattern classification systems", International Journal of Approximate Reasoning, vol. 35, no. 3, pp.251-273, 2004 [.pdf]

  • Gabrys, B., “Learning Hybrid Neuro-Fuzzy Classifier Models From Data: To Combine or not to Combine?”, Fuzzy Sets and Systems, vol. 147, pp. 39-56, 2004. [.pdf]

  • Petrakieva, L. and B. Gabrys, "Selective Sampling for Combined Learning from Labelled and Unlabelled Data", A selected paper in the book on "Applications and Science in Soft Computing" published in the Springer Series on Advances in Soft Computing, Lotfi, A. and Garibaldi, J. M. (Eds.), ISBN: 3-540-40856-8, pp. 139-148, 2004.

  • Ruta, D. and B.Gabrys, "Physical Field Models for Pattern Classification", Soft Computing, vol. 8, no. 2, pp. 126-141, 2003. [.pdf]

  • Gabrys, B., “Neuro-Fuzzy Approach to Processing Inputs with Missing Values in Pattern Recognition Problems”, International Journal of Approximate Reasoning, vol. 30, no. 3, pp. 149-179, 2002. [.pdf]

  • Gabrys, B., “Agglomerative Learning Algorithms for General Fuzzy Min-Max Neural Network”, the special issue of the Journal of VLSI Signal Processing Systems entitled  "Advances in Neural Networks for Signal Processing", vol. 32, no. ½, pp. 67-82, 2002. [.pdf]

  • Ruta, D. and B. Gabrys, "A Theoretical Analysis of the Limits of Majority Voting Errors for Multiple Classifier Systems", Pattern Analysis and Applications, vol. 5, pp. 333-350, 2002. [.pdf]

  • Ruta, D. and B. Gabrys, "Set Analysis of Coincident Errors and Its Applications for Combining Classifiers", In“Pattern Recognition and String Matching” (Eds. D.Chen and X.Cheng), ISBN 1-4020-0953-4, Kluwer Academic Publishers, Dec 2002. [.pdf]

  • Ruta, D. and B.Gabrys, "An Overview of Classifier Fusion Methods", Computing and Information Systems, University of Paisley, ISSN 1352-9404, Vol. 7, No. 1, pp. 1-10, February 2000. [.pdf]

  • Gabrys B. and Bargiela A., "General Fuzzy Min-Max Neural Network for Clustering and Classification", IEEE Transactions on Neural Networks, Vol. 11, No. 3, pp. 769-783, 2000. [.pdf]

  • Gabrys B. and Bargiela A., "Analysis of Uncertainties in Water Systems Using Neural Networks", MEASUREMENT + CONTROL, Vol. 32, No. 5, pp. 145-147, 1999.

  • Gabrys B. and Bargiela A., "Neural Networks Based Decision Support in Presence of Uncertainties", ASCE J. of Water Resources Planning and Management, Vol. 125, No. 5, pp. 272-280, 1999.

Refereed conference proceedings

  • Kadlec, P. and B. Gabrys, “Adaptive on-line prediction soft sensing without historical data”. Submitted to the World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain. 2010. (submitted)

  • Budka, M. and Gabrys, B., “Correntropy-based density-preserving data sampling as an alternative to standard cross-validation”, Submitted to the World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain. 2010. (submitted)

  • Lemke, C. and B. Gabrys, “Meta-learning for time series forecasting in the NN GC1 competition”, Submitted to the World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain. 2010. (submitted)

  • Budka, M. and Gabrys, B., “Ridge regression ensemble for toxicity prediction”, Accepted to the Tenth International Conference on Computational Science (ICCS 2010), Amsterdam, The Netherlands, May 31 - June 2, 2010.

  • Gabrys, B., “Robust adaptive soft sensors for process industry”, Invited contribution to the CISIS 2009 conference, Burgos, Spain, Sep. 2009.

  • Gabrys, B., “Learning with Missing or Incomplete Data”, Invited contribution. Invited contribution to the 15th International Conference on Image Analysis and Processing (ICIAP’2009). Vietri, Italy, Sep. 2009.

  • Eastwood, M. and B. Gabrys, “A Non-Sequential Representation of Sequential Data for Churn Prediction”, Proceedings of the KES’2009 conference, Santiago, Chile, Sep 2009.

  • Budka, M. and B. Gabrys, “Electrostatic Field Classifier for Deficient Data”, Proceedings of the CORES’2009 conference. Jelenia Gora, Poland, May 2009.

  • Kadlec, P. and B. Gabrys, “Evolving on-line prediction model dealing with industrial data sets”, Proceedings of the IEEE Symposium Series on Computational Intelligence 2009. March 2009.

  • Lemke, C. and B. Gabrys, “Dynamic Combination of Forecasts Generated by Diversification Procedures Applied to Forecasting of Airline Cancellations”, Proceedings of the IEEE Symposium Series on Computational Intelligence 2009. March 2009.

  • Gabrys, B., “Self-adapting architecture for building powerful predictive models”. Invited contribution to ICONIP’2008 conference. Nov 2008.

  • Musial K., Juszczyszyn K., Gabrys B. and Kazienko P.  "Patterns of Interactions in Complex Social Networks based on Coloured Motifs Analysis", Proceedings of ICONIP’2008 conference. Auckland, New Zealand. 25-28 Nov. 2008.

  • Kadlec, P. and B. Gabrys, “Adaptive Local Learning Soft Sensor for Inferential Control Support”, Proceedings of the CIMCA’2008 conference. Vienna, Austria. Dec 2008.

  • Kadlec, P. and B. Gabrys, “Soft Sensor based on adaptive local learning”, Proceedings of ICONIP’2008 conference. Auckland, New Zealand. 25-28 Nov. 2008.

  • Juszczyszyn K., Kazienko P., Musial K., and Gabrys B., "Temporal Changes in Connection Patterns of an Email-based Social Network", Proceedings of the IEEE/WIC/ACM Joint International Conference on Web Intelligence and Intelligent Agent Technology 2008, Sydney, Australia, 9-12 Dec 2008, 2nd Workshop on Collective Intelligence in Semantic Web and Social Networks (CISWSN 2008), IEEE Computer Society Press, 2008

  • Lemke, C. and B. Gabrys, "On the benefit of using time series features for choosing a forecasting method". Proceedings of the 2nd European Symposium on Time Series Prediction, Porvoo, Finland, 17-19 Sep 2008.

  • Kadlec, P. and B. Gabrys, "Learnt Topology Gating Artificial Neural Networks", Proceedings of the International Joint Conference on Neural Networks (IJCNN 2008) as part of the 2008 IEEE World Congress on Computational Intelligence (WCCI'2008), ISBN: 978-1-4244-1821-3, pp. 2605-2612, Hong Kong, June 2008. [.pdf]

  • Lemke, C. and B. Gabrys, "Do we need experts for time series forecasting?", Proceedings of the 16th European Symposium on Artificial Neural Networks (ESANN'2008), Bruges, Belgium, April 2008. [.pdf]

  • Kadlec, P. and B. Gabrys, "Nature-inspired Adaptive Architecture for Soft Sensor Modelling", Proceedings of the NiSIS'2007 Symposium, Malta, Nov 2007.

  • Lemke, C. and B. Gabrys, "Review of Nature-inspired Forecast Combination Techniques", Proceedings of the NiSIS'2007 Symposium, Malta, Nov 2007.

  • Ruta, D. and B.Gabrys, "Reducing Spatial Data Complexity for Classification Models", COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING: Theory and Computation: Old Problems and New Challenges. Lectures Presented at the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007). Vol. 1. American Institute of Physics Conference Proceedings, vol. 963, pp. 603-613, September 2007. [.pdf]

  • Sahel, Z, A.Bouchachia, B. Gabrys and P. Rogers, "Adaptive Mechanisms for Classification Problems with Drifting Data", Proceedings of the 11th International Conference on Knowledge-based Intelligent Engineering Systems (KES'2007), Lecture Notes in Computer Science (LNCS), ISBN: 978-3-540-74826-7, pp. 419-426, Vietri sul Mare, Italy, September 2007.

  • Riedel, S. and B. Gabrys, "Dynamic Pooling for the Combination of Forecasts generated using Multi Level Learning", Proceedings of the International Joint Conference on Neural Networks (IJCNN'2007), ISBN: 978-1-4244-1380-5, pp. 454-459, Orlando, Florida, USA, August 2007. [.pdf]

  • Ruta, D. and B.Gabrys, "Neural Network Ensembles for Time Series Prediction", Proceedings of the International Joint Conference on Neural Networks (IJCNN'2007), ISBN: 978-1-4244-1380-5, pp. 1204-1209, Orlando, Florida, USA, August 2007. [.pdf]

  • Bouchachia, A., B. Gabrys and Z. Sahel, "Overview of Some Incremental Learning Algorithms", Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'2007), ISBN: 1-4244-1210-2, pp. 1-6, London, UK, July 2007.

  • Macas, M, B. Gabrys, D. Ruta, and L. Lhotska, "Particle Swarm Optimisation of Multiple Classifier Systems", Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN'2007), Lecture Notes in Computer Science (LNCS), ISBN: 978-3-540-73006-4, pp. 333-340, San Sebastián, Spain, June 2007.

  • Eastwood, M. and B. Gabrys, "Lambda as a Complexity Control in Negative Correlation Learning", Proceedings of the NiSIS'2006 Symposium, Tenerife, Spain, Nov 2006.

  • Baruque, B., E. Corchado, B. Gabrys, Á. Herrero, J. Rovira, J. Gonzalez, "Unsupervised Ensembles Techniques for Visualization", Proceedings of the NiSIS'2006 Symposium, Tenerife, Spain, Nov 2006.

  • Gabrys, B., B. Baruque and E. Corchado, "Outlier Resistant PCA Ensembles", Proceedings of the KES'2006 conference, Lecture Notes in Computer Science (LNCS), ISBN: 978-3-540-46542-3, pp. 432-440, Bournemouth, UK, Oct 2006.

  • Apeh, E. and B. Gabrys, "Clustering for Data Matching", Proceedings of the KES'2006 conference, Bournemouth, Lecture Notes in Computer Science (LNCS), ISBN: 978-3-540-46535-5, pp. 1216-1225, UK, Oct 2006.

  • Corchado, E., B. Baruque and B. Gabrys, "Maximum Likelihood Topology Preserving Ensembles", Proceedings of the IDEAL'2006 conference, Lecture Notes in Computer Science (LNCS), ISBN: 978-3-540-45485-4, pp. 1434-1442, Burgos, Spain, Sep 2006.

  • Riedel, S. and B. Gabrys, "Evolving Multilevel Forecast Combination Models - An Experimental Study", Proceedings of NiSIS'2005 Symposium, Albufeira, Portugal, Oct 2005.

  • Ruta, D. and B. Gabrys, "Nature-inspired Learning Models", Proceedings of NiSIS'2005 Symposium, Albufeira, Portugal, Oct 2005.

  • Riedel, S. and B. Gabrys, "Hierarchical Multilevel Approaches of Forecast Combination", Proceedings of the OR'2004 conference, Netherlands, 2004.

  • Riedel, S. and B. Gabrys, "Adaptive Mechanisms in an Airline Ticket Demand Forecasting System", Proceedings of the EUNITE'2003 conference, Oulu, Finland, 2003.

  • Petrakieva, L. and B. Gabrys, “Selective Sampling for Combined Learning from Labelled and Unlabelled Data”, Proceedings of RASC’2002 Conference, Nottingham, UK, Dec. 2002.

  • Gabrys, B. and L. Petrakieva, “Combining labelled and unlabelled data in the design of pattern classification systems”, Proceedings of EUNITE’2002 conference, Hybrid Methods for Adaptive Systems (HMAS’2002) workshop, Albufeira, Portugal, Sep. 2002.

  • Ruta, D. and B. Gabrys, “New Measure of Classifier Dependency in Multiple Classifier Systems”, Proceedings of the MCS’2002 conference, Italy, June 2002. [.pdf]

  • Gabrys, B., "Combining Neuro-Fuzzy Classifiers for Improved Generalisation and Reliability", Proceedings of the Int. Joint Conference on Neural Networks , (IJCNN’2002) a part of the WCCI’2002 Congress, ISBN: 0-7803-7278-6, pp. 2410-2415, Honolulu, USA, May 2002. [.pdf]

  • Ruta, D. and B. Gabrys, "Static Field Approach for Pattern Classification", Proceedings of the Soft-Ware 2002 Conference, ISBN 3-540-43481, pp. 232-246, Belfast, UK, April 2002.

  • Gabrys, B., "Learning Hybrid Neuro-Fuzzy Classifier Models From Data: To Combine or not to Combine?", Proceedings of the EUNITE'2001 Conference, Tenerife, Spain, December 2001.

  • Ruta, D. and B.Gabrys , “The Boundaries of Knowledge”, Computing and Information Systems, (Ed. Prof. M. Crowe), University of Paisley, ISSN 1352-9404, Vol. 8, No. 3b, pp. 109-110 , October 2001.

  • Gabrys, B., “Data Editing for Neuro-Fuzzy Classifiers”, Proceedings of the SOCO/ISFI’2001 Conference, ISBN: 3-906454-27-4, Abstract page 77, Paper no. #1824-036, Paisley, UK, June 2001. [.pdf]

  • Ruta, D. and B. Gabrys , “Application of the evolutionary algorithms for classifier selection in multiple classifier systems with majority voting”, Proceedings of the MCS’2001 Workshop, Cambridge, UK, ISBN 3-540-42284-6, pp. 399-408, July 2001. [.pdf]

  • Ruta, D. and B. Gabrys , “Analysis of the correlation between majority voting error and the diversity measures in multiple classifier systems”, Proceedings of the SOCO/ISFI’2001 Conference, ISBN: 3-906454-27-4, Abstract page 50, Paper no. #1824-025,  Paisley, UK, June 2001.

  • Gabrys, B., "Agglomerative Learning for General Fuzzy Min-Max Neural Network", Procceedings of the IEEE NNSP’2000 Workshop, Sydney, ISBN 0-7803-6278-0, pp. 692-701, December 2000.

  • Gabrys, B., "Pattern Classification for Incomplete Data", Proceedings of 4th International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies KES'2000, Brighton, ISBN 0-7803-6400-7, Vol.1, pp. 454-457, August 2000.

  • Fyfe C. and Gabrys B., "E-insensitive Unsupervised Learning", Proceedings of International Conference on Neural Networks and Artificial Intelligence ICNNAI'99, Brest, ISBN 985-6584-05-1, pp. 10-18, October 1999.

  • Gabrys B. and Bargiela A., "Simulation of Water Distribution Systems", Proceedings of European Simulation Symposium ESS'98, Nottingham, ISBN 1-56555-147-8, pp.273-277, 1998.

  • Gabrys B., Bargiela A., "Integrated Neural Based System for State Estimation and Confidence Limit Analysis in Water Networks", Proceedings of European Simulation Symposium ESS'96, Genoa, ISBN 1-565555-099-4 (Vol.2), pp.398-402, October 1996. [.pdf]

  • Gabrys B., Bargiela A., "Neural Simulation of Water Systems for Efficient State Estimation", Proceedings of Modelling and Simulation Conference ESM'95, Prague, Eds. M Snorek, M Sujansky, A Verbraeck, ISBN 1-56555-080-3, pp. 775-779, June 1995.

  • Gabrys B., "Application of Orthogonal Method for Simulation of Deep Bed Filtration Process", Proceedings of Modelling and Simulation Conference ESM'94, Barcelona, 1994.

Theses

  • Gabrys B., Neural Network Based Decision Support: Modelling and Simulation of Water Distribution Networks, PhD Thesis, The Nottingham Trent University, 1997.

  • Gabrys, B., Neural Networks for Solving Systems of Linear Equations, MSc Thesis (in Polish), The Silesian Technical University, 1994.

Selected presentations

  • Plenary talk on “Robust adaptive soft sensors for process industry” at the CISIS 2009 conference, Burgos , Spain, September 2009.

  • Plenary talk on "The missing data in pattern recognition problems" at the 15th International Conference on Image Analysis and Processing (ICIAP 2009), Vietri sul Mare, Salerno, Italy, 8-11 September 2009.

  • An invited keynote talk on “Self-adapting architecture for building powerful predictive models” at the 15th International Conference on Neural Information Processing (ICONIP 2008), Auckland, New Zealand, 24-27 Nov 2008.

  • Opening plenary talk at the 3 rd International Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008), Burgos, Spain, 24-26 September 2008.

  • Invited research seminar at the InfoLab21 in Lancaster University, Lancaster, UK, 18 September 2008.

  • Series of invited lectures on “Multiple classifier and prediction systems” at the Wroclaw University of Technology, Wroclaw, Poland, June 2008.

  • Series of invited lectures on “Smart adaptive systems” at the Wroclaw University of Technology, Wroclaw, Poland, May 2008.

  • An invited keynote talk at the Knowledge Processing and Reasoning for Information Society Workshop, Wroclaw, Poland, Feb 2008.

  • Plenary talk invitation to the International Conference on Soft Computing and Intelligent Systems (ICSCIS 2007), Jabalpur, India, 27-29 Dec 2007.

  • An invited keynote talk to be delivered at the World Congress on Engineering (WCE'2007), London, U.K., 2-4 July 2007.

  • An invited keynote talk to be delivered at the European Conference on Data Mining (ECDM'2007) as part of the IADIS Multi Conference on Computer Science and Information Systems 2007 (http://www.mccsis.org), Lisbon, Portugal, 6-8 July 2007.

  • 3 invited keynote talks at the International Scientists IT Workshop Series at: a) the Catholic University of Daegu, Daegu, 13th Nov; b) the Hannam University, Daejeon, 14th Nov; and the Inha University, Incheon, 15th Nov, South Korea, Nov 2006.

  • An invited keynote talk given at the 2006 International Forum on ALife and Adaptive Robotics at the ITRC-Intelligent Robot Research Center at the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea, 8-9 Nov 2006.

  • Do Smart Adaptive Systems Exist? - Soft computing perspective. An invited plenary talk presented at the international conference on Recent Advances in Soft Computing (RASC'2006), Canterbury, UK, July 2006.

  • Do smart adaptive systems exist?- Hybrid intelligent systems perspective. An invited keynote talk given at the summer school at the University of Burgos, Burgos, Spain, July 2006.

  • To combine or not to combine? - Multiple classifier and prediction systems. An invited keynote talk given at the summer school at the University of Burgos, Burgos, Spain, July 2006.

  • Do smart adaptive systems exist?. An invited keynote talk given at the University of Brighton's Engineering Research in Action (ERA) day, Brighton, UK, 13th June 2006.

  • Multiple Classifier Systems - Issues, Motivations and Challenges. A seminar talk given at the Informatics Institute, University of Exeter, Exeter, UK, 21st of April 2006.

  • Do Smart Adaptive Systems Exist?, An invited keynote talk given at the workshop on "Adaptive Systems - Advanced Issues", Southampton, UK, 24th Feb 2006.

  • Overview of Research Interests, Projects and Activities in the Computational Intelligence Research Group. A talk given at the start of a new series of computing seminars at the School of DEC, Bournemouth, UK. 15 Feb 2006.

  • Multiple Classifier Systems - Issues, Motivations and Challenges. A seminar talk given as part of the School of DEC seminar series, Bournemouth, UK, 18 Jan 2006.

  • Multilevel Classifier Systems - Issues, Motivations and Challenges. An invited talks given at the Centre for Intelligent Agents and Multi-Agent Systems (CIAMAS) at the Swinburne University of Technology, Melbourne, Australia, 5 Sep 2005

  • Multilevel Classifier Systems - Issues, Motivations and Challenges.
    An invited talk given at the Monash Data Mining Centre (MDMC) at the Monash University, Melbourne, Australia, 13 Sep 2005

  • Multilevel Classifier Systems - Issues, Motivations and Challenges. An invited talk given at the Bioinformatics Applications Research Centre (BARC) at the James Cook University, Townsville, Australia, 21 Sep 2005

  • Multilevel Prediction and Classification Systems. An invited talk given at the University of Magdeburg, Magdeburg, Germany, 12 May 2005

  • Multilevel Prediction and Classification Systems. An invited talk given at the University of Konstanz, Konstanz, Germany, 11 May 2005

  • Hybrid intelligent methods and smart adaptive systems. An invited lecture given at the University of Burgos, Burgos, Spain, 15 April 2005

  • Multiple classifier systems: issues, motivations and challenges. An invited lecture given at the University of Burgos, Burgos, Spain, 14 April 2005

  • General Fuzzy Min-Max neural Networks for Clustering and Classification. An invited lecture given at the University of Burgos, Burgos, Spain, 14 April 2005

  • Multiple Classifier Systems: Issues, motivations and challenges. An invited talk given at Auckland University, Auckland, New Zealand, 17th Sep, 2004

  • Multiple Classifier Systems: Issues, motivations and challenges. An invited talk given at the Wellington Institute of Technology, Wellington, New Zealand, 10th Sep, 2004

  • Hybrid Intelligent Methods and Smart Adaptive Systems. A plenary talk given at the EUNITE'2004 conference. June 2004

  • MultipleClassifier Systems: Issues, motivations and challenges. An invited talk given at the Electronic Engineering Laboratory, University of Kent, Canterbury, UK,18th Feb, 2004

  • MultipleClassifier Systems: Issues, motivations and challenges. An invited talk given at the Computing Laboratory, University of Oxford, Oxford, UK, 2nd Dec, 2003

  • MultipleClassifier Systems: Issues, motivations and challenges. An invited talk given at the School of Computer Science, University of Birmingham, Birmingham, UK, 20th Oct, 2003

  • Multiple Classifier Systems: Issues, motivations and challenges. An invited talk given at the School of Computer Science & Information Technology, Nottingham University, Nottingham, UK, 26th Mar, 2003

  • Multiple Classifier Systems: Motivations and Challenges. An invited talk given at the Intelligent Systems Labs of BTexact, Ipswich, UK, 31st Jan, 2003

  • Combining labelled and unlabelled data in the design of pattern classification systems. A paper presented at Hybrid Methods for Adaptive Systems (HMAS'2002) workshop, Albufeira, Portugal, 20th Sep, 2002

  • Combining Neuro-Fuzzy Classifiers for Improved Generalisation and Reliability. A paper presented at WCCI'2002 Congress, Honolulu, USA, 16th May, 2002

  • Multiple Classifier Systems. An invited talk given at the Department of Enterprise Integration, Cranfield University. Cranfield, UK, 8th Mar. 2002

  • Learning Hybrid Neuro-Fuzzy Classifier Models From Data: To Combine or not to Combine?. A paper presented at the EUNITE'2001 Conference. Tenerife, Spain, 13th Dec. 2001

  • Data and Information Fusion. An invited talk given at the Lufthansa Systems Berlin GmbH, Berlin, 4th Dec. 2001

  • Data Editing for Neuro-Fuzzy Classifiers.  A paper presented at  SOCO’2001 Conference, Paisley, 2001

  • Agglomerative Learning for General Fuzzy Min-Max Neural Network. A paper presented at IEEE NNSP’2000 Workshop. Sydney. 13th Dec. 2000

  • Fuzzy neural networks for clustering and classification and their use in a diagnostic system for leakage detection and location in water distribution systems. An invited talk given at the Control Systems Centre, UMIST University. Manchester, 15th Nov. 2000

  • Pattern Classification for Incomplete Data. A paper presented at the KES’2000 conference. Brighton. 31st Aug. 2000

  • E-insensitive Unsupervised Learning. A paper presented at the ICNNAI'99. Brest. Belarus. 13th Oct. 1999.

  • General Fuzzy Min-Max Neural Network for Clustering and Classification. A talk given at the Department of Computing and Information Systems of the University of Paisley. Paisley. Apr. 1999.

  • Simulation of Water Distribution Systems. A paper presented at the European Simulation Symposium ESS'98. Nottingham, UK. 27th Oct. 1998.

  • Neural networks applied to water systems monitoring and control. A talk given at the Department of Computing of the Nottingham Trent University. Nottingham. 22nd Jan. 1997.

  • Integrated neural based system for state estimation and confidence limit analysis. A paper presented at the European Simulation Symposium ESS'96. Genoa, Italy. 25th Oct. 1996.

  • Neural network based decision support system. A poster presentation given at The 6th Annual Cambridge Neural Networks Summer School. Cambridge, UK. 9th Sep. 1996.

  • Neural simulation of water systems for efficient state estimation. a paper presented at the International Modelling and Simulation Conference ESM'95. Prague, Czech Republic. 6th June 1995.

Copyright © 2002 B. Gabrys.
All rights reserved.