

Computational Intelligence (CI) methodologies, including evolutionary algorithms, neural networks and fuzzy systems have shown to be sell suited to deal with significant uncertainties that may be encountered in solving real-world problems. The purpose of this symposium is to bring together scientists, engineers, and graduate students to present and discuss recent advances in employing CI for solving scientific and engineering problems in the presence of uncertainties.
Topics of the interest include but are not limited to:
Yaochu Jin, University of Surrey, UK
Shenxiang Yang, Brunel University, UK
Robi Polikar, Rowan University, USA
Cesare Alippi, Politecnico di Milano, Italy
Dirk Arnold, Dalhousie University, Canada (TBC)
Hans-Georg Beyer, Vorarlberg University of Applied Sciences, Austria (TBC)
Gavin Brown, University of Manchester, UK
Tim Blackwell, Goldsmiths College London, UK (TBC)
Juergen Branke, University of Warwick, UK
Hui Cheng, University of Leicester, UK
Ernesto Costa, University of Coimbra, Portugal
Jing Gao, University of Illinois, Urbano Champaign, USA (TBC)
Chi-Keong Goh, Data Storage Institute, Singapore
Abdelhamid Bouchachia, University of Klagenfurt, Austria
Haibo He, University of Rhode Island , USA
Ivan Koychev, Bulgarian Academy of Sciences, Bulgaria
Xiaodong Li, RMIT University, Australia (TBC)
Yan Meng, Stevens Institute of Technology, USA
Ferrante Neri, University of Jyvaskyla, Finland
Yew-Soon Ong, Nanyang Technological University, Singapore (TBC)
Hendrik Richter, University of Leipzig, Germany
Philipp Rohlfshagen, University of Birmingham, UK
Moamar SAYED MOUCHAWEH, Université de Reims, France
Kay Chen Tan, National University of Singapore, Singapore (TBC)
Renato Tinos, Universidade de Sao Paulo, Brazil (TBC)
Sima Uyar, Istanbul Technical University, Turkey (TBC)
Hongfeng Wang, Northeastern University, China
Jeremy Watts, University of Birmingham, UK
Qingfu Zhang, University of Essex, UK
Indrė Žliobaitė, Vilnius University, Lithuania