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Edwin Lughofer

Edwin Lughofer's picture
edwin.lughofer@jku.at FLLL 043 (0) 7236 3343 - 431
  • PAC (K-Project): Process Analytical Chemistry - Data Acquistion and Data Processing (Key Researcher); National K-Project sponsored by the FFG, 9 industrial and 7 academic research partners
  • useML (FFG "IKT of the Future"): Improving the usability of machine learning in industrial inspection systems; in collaboration with the coordinator Profactor and 2 industrial partners (Key Researcher)
  • IREFS (bilateral FWF/DFG research project): Interpretable and Reliable Evolving Fuzzy Systems (Initiator)
  • Condition Monitoring with Data-Driven Models: Strategic Project with ACCM (Area 6) (Key Researcher)
  • Performance Optimization of Electrical Drives: Strategic Project with ACCM (Area 4) (Key Researcher)
  • ASHMOSD (National Research Project):  Austrian Structural Health Monitoring System Demonstrator
  • DynaVis (EU-Project): Dynamically adaptive image classification framework; combining machine learning with image processing techniques: www.dynavis.org; technical representative of JKU (Key Researcher)
  • SynteX (EU-Project): Measuring Feelings and Expectations Associated with Textures: www.syntex.or.at
  • Technology Transfer sponsored by the Upperaustrian technology and research promotion
  • AMPA (EU-Project): Automatic Measurement Plausibility Analysis at engine test benches: research and development in data-based modelling, nonlinear system identification and fault detection; technical representative of JKU (Key Researcher) in AMPA EU-Project; together with 8 partners in Europe
  • Exchange of know-how in data-driven evolving fuzzy systems with Lancaster University, sponsored by the Royal Society Grant, United Kingdom

 
Activities:

 
Books:
 

 
Book Chapters:
 

  • Edwin Lughofer, Flexible Evolving Fuzzy Inference Systems from Data Streams (FLEXFIS++), in: Learning in Non-Stationary Environments: Methods and Applications, editors: Moamar Sayed-Mouchaweh and Edwin Lughofer, Springer, New York, 2012, pp. 205-246
     
  • Edwin Lughofer, Christian Eitzinger and Carlos Guardiola, On-line Quality Control with Flexible Evolving Fuzzy Systems, in: Learning in Non-Stationary Environments: Methods and Applications, editors: Moamar Sayed-Mouchaweh and Edwin Lughofer, Springer, New York, 2012, pp. 375-406
     
  • Davy Sannen, Jean-Michel Papy, Steve Vandenplas, Edwin Lughofer and Hendrik van Brussel, Incremental Classifier Fusion and its Application in Industrial Monitoring and Diagnostics, in: Learning in Non-Stationary Environments: Methods and Applications, editors: Moamar Sayed-Mouchaweh and Edwin Lughofer, Springer, New York, 2012, pp. 153-184
     
  • Edwin Lughofer, Evolving Fuzzy Models - Incremental Learning, Stability and Interpretability Issues, Applications, VDM Verlag, Saarbrücken, 2008 (book issue of PhD thesis)
     
  • Edwin Lughofer, Data-Driven Incremental Learning of Takagi-Sugeno Fuzzy Models, PhD-Thesis, Department of Knowledge-Based Mathematical Systems, University Linz, 2001-2005

     

  • Edwin Lughofer. Towards Robust Evolving Fuzzy Systems, book chapter in Evolving Intelligent Systems - Methodologies and Applications, editors: Plamen Angelov, Dimitar Filev and Nik Kasabov, John Wiley and Sons, 2010, pp. 87-126
     
  • Erich Peter Klement*, Edwin Lughofer, Johannes Himmelbauer and Bernhard Moser, Data-Driven and Knowledge-Based Modelling, chapter in Hagenberg Research, editors: Michael Affenzeller, Bruno Buchberger, Alois Ferscha, Michael Haller, Tudor Jebelean, Erich Peter Klement, Josef Kueng, Peter Paule, Birgit Proell, Wolfgang Schreiner, Gerhard Weiss, Roland Wagner, Wolfram Woess, Robert Stubenrauch and Wolfgang Windsteiger, Springer Verlag, pp. 237-279, 2009
     
  • Christian Eitzinger*, James E. Smith, Edwin Lughofer and Davy Sannen, Lernfaehige Inspektionssysteme, Automatisierungsatlas, SPS Magazin, 2009, pp. 370-372

 

Position Papers and Editorials:

Journal Papers:

* corresponding author(s)
 
 
Selected Conference Papers (2006-2014):  (Full List)
 

  • F. Serdio, C. Zavoianu, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Hybrid Genetic-Fuzzy Systems for Improved Performance in Residual-Based Fault Detection, Proceedings of the 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC), to appear, Porto, Portugal, 2014
     
  • F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Reducing False Positives for Residual-Based On-line Fault Detection by Means of Adaptive Filters, Proceedings of the IEEE SMC 2014 Conference, San Diego, to appear, 2014
     
  • K. Pichler, M. Pichler, E. Lughofer, E.P. Klement, M.Huschenbett, T. Buchegger, On the robustness of fault detection in reciprocating compressor valves, Proceedings of the IEEE SMC 2014 Conference, San Diego, to appear, 2014
     
  • F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic. Gradient-based Fuzzy Fault Isolation in Residual-based Fault Detection Systems. Proceedings of the WCCI 2014 Conference, Bejing, China, to appear, 2014
     
  • M. Pratama, S.G. Anavatti, M.J. Er and E. Lughofer. A Novel Meta-Cognitive-based Scaffolding Classifier to Sequential Non-stationary Classification Problems.
    Proceedings of the WCCI 2014 Conference, Bejing, China, to appear, 2014
     
  • C. Cernuda, E. Lughofer, P. Hintenaus, W. Märzinger and J. Kasberger.
    Genetic Hybridization (Hybridgen): A Cooperative Coevolution Algorithm for Variable Selection. Proceedings of the CAC 2014 conference, Richmond, Virginia, 2014, to appear.
     
  • M. Pratama, S.G. Anavatti and E. Lughofer. An Incremental Classifier from Data Streams. in: A. Likas, K. Blekas, and D. Kalles (Eds.): SETN 2014, LNCS 8445, pp. 15--28, Springer International Publishing Switzerland, 2014.
     
  • C. Cernuda, E. Lughofer, P. Hintenaus, W. Maerzinger, T. Reischer and J. Kasberger, Fuzzy Finite State Machine for Multivariate Calibration. Application to Near-Infrared Spectroscopy, Proceedings of the EuroPACT conference, to appear Barcelona, Spain, 2014.
     
  • E. Lughofer, C. Cernuda and M. Pratama, Generalized Flexible Fuzzy Inference Systems from Data Streams, IEEE Conference on Machine Learning and Applications (ICMLA), pp 1-7, 2013
     
  • A.-C. Zavoianu, E. Lughofer, G. Bramerdorfer, W. Amrhein, and E.P. Klement,  Effective Ensemble-based Method for Creating On-the-Fly Surrogate Fitness Functions for Multi-Objective Evolutionary Algorithms, Proceedings of the 5th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) 2013, Timisoara, Romania, 2013
     
  • A.-C. Zavoianu, E. Lughofer, W. Amrhein and E.P. Klement, Efficient Multi-Objective Optimization using 2-Population Cooperative Coevolution, Proceedings of the EUROCAST 2013 Conference,Las Palmas de Gran Canaria, Spain, 2013
     
  • C. Cernuda, E. Lughofer, G. Mayr, T. Röder, P. Hintenaus, W. Märzinger and J. Kasberger, Decremental Active Learning for Optimized Self-Adaptive Calibration in Viscose Production, Proceedings of the SSC 2013 Conference, Stockholm, 2013
     
  • F. Serdio, E. Lughofer, K. Pichler, T. Buchegger, M. Pichler and H. Efendic, Multivariate Fault Detection in the Residual Space using VARMA and Orthogonal Transformations, PHM 2013 Conference, to appear, New Orleans, 2013
     
  • C. Cernuda, E. Lughofer, P. Hintenaus, W. Märzinger, T. Reischer, M. Pawliczek, J. Kasberger, Ensembled Self-Adaptive Fuzzy Calibration Models for On-line Cloud Point Prediction, Proceedings of the EUSFLAT 2013 conference, Milano, Italy, 2013, to appear
     
  • F. Serdio, E. Lughofer, K. Pichler, T. Buchegger and H. Efendic, Data-Driven Residual-Based Fault Detection for Condition Monitoring in Rolling Mills, Proceedings of the IFAC Conference on Manufacturing Modeling, Management and Control (MIM) 2013, St. Petersburg, 2013, to appear. (awarded as best paper)
     
  • K. Pichler, E. Lughofer, M. Pichler, T. Buchegger, E.P. Klement, M. Huschenbett, Detecting broken Reciprocating Compressor Valves in the pV-diagram, Proceedings of the 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, to appear, 2013
     
  • M. Pratama, S. Anavatti and E. Lughofer, Evolving Fuzzy Rule-Based Classifier Based on GENEFIS, Proceedings of the FUZZ-IEEE 2013 Conference, Hyderabad, India, 2013, to appear
     
  • C. Zavoianu, E. Lughofer, W. Koppelstaetter, G. Weidenholzer, W. Amrhein, E.P. Klement, On the Performance of Master-Slave Parallelization Methods for Multi-Objective Evolutionary Algorithms, Proceedings of the ICAISC 2013 conference, Zakopane, Poland, to appear
     
  • A. Shaker and E. Lughofer, Resolving Global and Local Drifts in Data Stream
    Regression using Evolving Rule-Based Models
    , 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) (under the scope of IEEE SSCI 2013 Conference), Singapore, pp. 9-16, 2013
     
  • E. Lughofer, eVQ-AM: An Extended Dynamic Version of Evolving Vector Quantization, 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) (under the scope of IEEE SSCI 2013 Conference), Singapore, pp. 40-47, 2013
     
  • M. Pratama, S. Anavatti, M. Garret and E. Lughofer, Online Identification of Complex Multi-Input-Multi-Output System Based on Generic Evolving Neuro-Fuzzy Inference System, 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) (under the scope of IEEE SSCI 2013 Conference), Singapore, pp. 106-113, 2013
     
  • C. Cernuda, E. Lughofer, W. Märzinger and W. Summerer. Hybrid evolutionary particle swarm optimization and ant colony optimization for variable selection. Application to near infrared spectroscopy. Proceedings of the 3rd World Conference on Information Technology 2012, to appear, Barcelona, Spain, 2012.
     
  • E. Lughofer. Navigating Interpretability Issues in Evolving Fuzzy Systems. Proceedings of the SUM 2012 Conference, Springer Lecture Notes, LNAI 7520, pp. 141--153, 2012.
     
  • A.C. Zavoianu, G. Bramerdorfer, E. Lughofer, W. Amrhein, E.P. Klement. A Hybrid Soft Computing Approach for Optimizing Design Parameters of Electrical Drives. Soft Computing Models in Industrial and Environmental Applications (Proceedings of the SOCO 2012 Conference), vol. 181, pp. 347--358, Springer, Berlin Heidelberg, 2012.
     
  • K. Pichler, E. Lughofer, T. Buchegger, E.P. Klement, M. Huschenbett. Detecting Cracks in Reciprocating Compressor Valves using Pattern Recognition in Frequency Space. Proceedings of the ASME 2012 Conference, to appear, Atlanta, 2012.
     
  • K. Pichler, E. Lughofer, T. Buchegger, E.P. Klement, M. Huschenbett. A Visual Method
    to Detect Broken Reciprocating Compressor Valves Under Varying Load Conditions.
    Proceedings of the 13th Mechatronics Forum International Conference, to appear, Linz, Austria, 2012.
     
  • C. Cernuda, E. Lughofer,W. Märzinger,W. Summerer. Waveband Selection in NIR Spectra using Enhanced Genetic Operators. Proceedings of the CAC 2012 conference, Budapest, 2012, to appear.
     
  • C. Cernuda, E. Lughofer, L. Suppan, T. Röder, R. Schmuck, P. Hintenaus, W. Märzinger,
    J. Kasberger. Dynamic Quantification of Process Parameters in Viscose Production with Evolving Fuzzy Systems. Proceedings of the IPMU 2012, to appear, 2012.
     
  • Edwin Lughofer. On-line Active Learning with Enhanced Reliability Concepts. Proceedings of the IEEE EAIS (Evolving and Adaptive Intelligent Systems) Conference, Madrid, 2012.
     
  • Edwin Lughofer, Dynamic Evolving Cluster Models Using On-line Split-and-Merge Operations, Proc. of the 10th International Conference in Machine Learning and Applications (ICMLA) 2011, Honolulu, Hawaii, 2011, pp. 20--26, 2011.
     
  • Edwin Lughofer, Eyke Hüllermeier, On-line Redundancy Deletion in Evolving Fuzzy Regression Models using a Fuzzy Inclusion Measure, Proceedings of the EUSFLAT-LFA Conference, Aix-Les-Bains, 2011, pp. 380--387.
     
  • Edwin Lughofer, All-Pairs Evolving Fuzzy Classifiers for On-line Multi-Class
    Classification Problems
    , Proceedings of the EUSFLAT-LFA Conference, Aix-Les-Bains, 2011, pp. 372--379.
     
  • Maryam Nasiri, Eyke Hüllermeier, Robin Senge, Edwin Lughofer, Comparing Methods for Knowledge-Driven and Data-Driven Fuzzy Modeling: A Case Study in Textile Industry, Proceedings of the IFSA World Congress, Surabaya and Bali Islands, Indonesia, 2011.
     
  • Edwin Lughofer, Bogdan Trawiński, Krzysztof Trawiński, Tadeusz Lasota, On-line Valuation of Residential Premises with Evolving Fuzzy Models, Proceedings of the HAIS 2011 conference, LNAI 6678, Wroclaw, Poland, 2011, pp. 107-115.
     
  • Wolfgang Heidl, Stefan Thumfart, Christian Eitzinger, Edwin Lughofer, Erich Peter Klement, Decision Tree-Based Analysis Suggests Structural Gender Differences in Visual Inspection, Proceedings of the IASTED Artificial Intelligence and Applications (AIA) Conference 2011, Innsbruck, Austria, pp. 142-149.
     
  • Edwin Lughofer, On Dynamic Selection of the Most Informative Samples in Classification Problems, Proc. International Conference on Machine Learning and Applications (ICMLA) 2010, Washington DC, pp. 573-579
     
  • Edwin Lughofer, On Dynamic Soft Dimension Reduction in Evolving Fuzzy Classifiers, 13th International Conference on Information Processing and Management of Uncertainty, IPMU 2010,  Lecture Notes in Artificial Intelligence, LNAI 6178 (eds. E. Huellermeier, R. Kruse and F. Hoffmann), pp. 79-88, Dortmund, 2010
     
  • Davy Sannen, Edwin Lughofer, Hendrik van Brussel, Increasing Online Classification Performance Using Incremental Classifier Fusion, Proceedings of the International Conference on Adaptive and Intelligent Systems (ICAIS) 2009, pp. 101-107, Klagenfurt, Austria, 2009
     
  • Edwin Lughofer and Stefan Kindermann13. Rule Weight Optimization and Feature Selection in Fuzzy Systems with Sparsity Constraints, Proceedings of the IFSA/EUSFLAT 2009 conference, Lisbon, Portugal, 2009, pp. 950-956
     
  • Edwin Lughofer. Evolving Vector Quantization for Classification of On-Line Data Streams, Proc. of the International Coference on Computational Intelligence for Modelling, Control and Automation (CIMCA), pp. 780-786, Vienna, 2008
     
  • Christian Eitzinger, M. Gmainer, Wolfgang Heidl and Edwin Lughofer. Increasing Classification Robustness with Adaptive Features, in International Conference on Computer Vision Systems 2008, A. Gasteratos, M. Vincze, J.K. Tsotsos (Eds.), Springer Lecture Notes 5008, pp. 445-453, Santorini Island, Greece
     
  • D. Sannen, M. Nuttin, J.E. Smith, M.A. Tahir, P. Caleb-Solly, E. Lughofer, C. Eitzinger. An On-Line Self-Adaptive and Interactive Image Classification Framework, in International Conference on Computer Vision Systems 2008, A. Gasteratos, M. Vincze, J.K. Tsotsos (Eds.), Springer Lecture Notes 5008, pp. 171-180, Santorini Island, Greece
     
  • Edwin Lughofer and Carlos Guardiola. Applying Evolving Fuzzy Models with Adaptive Local Error Bars to On-Line Fault Detection, in Proc. of the 3rd International Workshop on Genetic and Evolving Fuzzy Systems, GEFS 2008, pp. 35-40, Witten-Bommerholz (Germany) (awarded as best paper finalist)
     
  • Edwin Lughofer, Plamen Angelov and Xiaowei Zhou. Evolving single- and multi-model fuzzy classifiers with FLEXFIS-CLASS, in Proceedings of FUZZ-IEEE 2007, pp. 363-368, London, UK, 2007 (cited 31 times)
     
  • Edwin Lughofer. Process safety enhancements for data-driven evolving fuzzy models. In Proceedings of the International Symposium on Evolving Fuzzy Systems (EFS), pp. 42-48, Lake District, UK, September 2006 (awarded as best paper)
     

 
Research Visits/Stays: