The 2015 International Conference on Intelligence Science and Big Data Engineering (IScIDE 2015) aims at a collective venue for introducing world frontier researchers to China and for introducing researchers of an ever developing and huge population of Chinese colleagues to international communities. This meeting is scheduled as the fifth of a serial annual meetings that promotes academic exchange of researches on various areas of intelligence science and intelligent data engineering in China and abroad, and will be held in Suzhou.

IScIDE 2015 is intended to have a broad scope, including information theoretic and Bayesian approaches, probabilistic graphical models, Big data analysis, neural networks and neuro-informatics, bioinformatics and computational biology, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning. Submissions will be rigorously reviewed, and should clearly make the case for a documented improvement over the existing state of the art. Experimental results for contributions in established areas such as speech, face, iris and gait are encouraged to use the largest and most challenging existing publicly available datasets.

All of the accepted papers of IScIDE 2012 and IScIDE 2013 have been published in Springer’s LNCS (EI indexed), and the selected papers have been published as special issues of Neurocomputing (SCI indexed). Moreover, the selected papers of IScIDE 2013 are also published in a special issue of International Journal of Computer Mathematics (SCI indexed) and a special issue of Computational and Mathematical Methods in Medicine (SCI indexed). These traditions will also be kept for IScIDE 2015.

The submission covers various topics that include, but are not limited to:
Information theoretic and Bayesian approaches
Probabilistic graphical models
Neural networks and neuro-informatics
Bioinformatics and computational biology
Pattern recognition and computer vision
Signal processing and image processing
Machine learning and computational intelligence
Data mining and information retrieval
Speech recognition and natural language processing
Big data analysis