Monday, 17 November 2014


Special Session for IEEE IJCNN 2015.

Updated submission deadline: 5th February, 2015.

One of the fundamental goals in computational intelligence is to achieve brain-like intelligence, a remarkable property of which is the ability to incrementally learn from noisy and incomplete data, and ability to adapt to changing environments. The special session aims at presenting novel approaches to incremental learning and adaptation to dynamic environments both from the more traditional and theoretical perspective of computational intelligence and from the more practical and application-oriented one.

This Special Session aspires at building a bridge between academic and industrial research, providing a forum for researchers in this area to exchange new ideas with each other, as well as with the rest of the neural network & computational intelligence community.

The Special Session will be held within the IEEE International Joint Conference on Neural Networks (IJCNN 2015), in Killarney, Ireland, on July 12-17, 2015

Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics:
  • Architectures, techniques and algorithms for learning in non-stationary/dynamic environments
  • Domain adaptation, dataset shift, covariance shift
  • Incremental learning, lifelong learning, cumulative learning
  • Change-detection tests and anomaly-detection algorithms
  • Mining from streams of data
  • Applications that call for incremental learning or learning in non-stationary/dynamic environments, such as:
    • Adaptive classifiers for concept drift and recurring concepts
    • Intelligent systems operating in non-stationary/dynamic environments
    • Intelligent embedded and cyber-physical systems
  • Applications that call for change and anomaly detection, such as:
    • fault detection
    • fraud detection
    • network intrusion and security
    • intelligent sensor networks
  • Cognitive-inspired approaches to adaptation and learning
  • Development of test-sets benchmarks for evaluating algorithms learning in non-stationary/dynamic environments
  • Issues relevant to above mentioned or related fields


Concept drift, nonstationary environment, change/anomaly detection, domain adaptation, incremental learning, data streams. 

Important dates

Paper Submission: February 5th, 2015
Notifications to Authors: March 15th, 2015
Final Submission: April 15th, 2015
Conference Dates: July 12 - 17th, 2015

Paper Submission

Submissions should contain original, high quality, not submitted or published elsewhere work. Papers will be included in the IEEE IJCNN 2015 proceedings.

Information concerning paper submission and manuscript preparation can be found at the IEEE IJCNN 2015 webpage for paper submission .

Please make sure you select the the Special Session 12 "Concept Drift, Domain Adaptation & Learning in Dynamic Environments" from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list during the submission process.


Giacomo Boracchi, Politecnico di Milano, Italy

Giacomo Boracchi received the M.S. degree in Mathematics from the Universit`a Statale degli Studi di Milano, Italy, and the Ph.D. degree in Information Technology at Politecnico di Milano, Italy, in 2004 and 2008, respectively. He was researcher at Tampere International Center for Signal Processing, Finland, during 2004-2005.

Currently, he is an assistant professor at the Dipartimento di Elettronica, Informazione e Bioingegneria of the Politecnico di Milano. His main research interests are design for embedded systems for nonstationary environments as well as mathematical and statistical methods for signal and image processing. He was a co-chair of 2014 IEEE Symposium on Intelligent Embedded Systems (IES 2014), part of the IEEE Symposium Series on Computational Intelligence.

Robi Polikar, Rowan University, NJ (USA).

is a Professor of Electrical and Computer Engineering at Rowan University, in Glassboro, NJ. He has received his B.Sc. degree in electronics and communications engineering from Istanbul Technical University, Istanbul, Turkey in 1993, and his M.Sc and Ph.D. degrees, both co-majors in electrical engineering and biomedical engineering, from Iowa State University, Ames, IA in 1995 and 2000, respectively.

His current research interests within computational intelligence include ensemble systems, incremental and nonstationary learning, and various applications of pattern recognition in bioinformatics and biomedical engineering. He is a member of IEEE, ASEE, Tau Beta Pi and Eta Kappa Nu. His current and prior works are funded primarily through NSF's CAREER and Energy, Power and Adaptive Systems (EPAS) programs. He has been heavily involved with IJCNN for over a decade with many special sessions, as well as serving as part of organizing committee. He is also an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems.

Manuel Roveri, Politecnico di Milano, Italy

received the Dr.Eng. degree in Computer Science Engineering from the Politecnico di Milano (Milano, Italy) in June 2003, the MS in Computer Science from the University of Illinois at Chicago (Chicago, Illinois, U.S.A.) in December 2003 and the Ph.D. degree in Computer Engineering from Politecnico di Milano (Milano, Italy) in May 2007.

Currently, he is an assistant professor at the Departent of Electroncis and Information of the Politecnico di Milano. His research interests include intelligent embedded systems, computational intelligence and adaptive algorithms. Manuel Roveri is an Associate Editor of the IEEE Transactions on Neural Networks and Learning Systems and served as chair and member in many IEEE subcommittees.

Technical Program Committee

  • Cesare Alippi, Politecnico Milano, Italy
  • Alfred Bifet, University of Waikato, New Zealand
  • Gianluca Bontempi, Université Libre de Bruxelles, Belgium
  • Gregory Ditzler, Drexel University, PA, USA
  • Yaochu Jin, University of Surrey, England, UK
  • Georg Krempl, University Magdeburg, Germany
  • Ludmilla Kuncheva, University of Bangor, Wales, UK
  • Leandro L. Minku, University of Birmingham, England, UK
  • Harris Papadopoulos, Frederick University, Cyprus
  • Leszek Rutkowski, Czestochowa University of Technology, Poland
  • Marley Vellasco, Pontifícia Universidade Católica do Rio de Janeiro, Brasil
  • Shengxiang Yang, Brunel University, England, UK

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