Big Data is becoming one of the hottest topics in current research in computer science, data mining, engineering, and applicable mathematics. There are many challenging issues associated with Big Data, and one very important issue is the high-dimensional data. Even with moderate size data, high-dimensionality can pose extra challenge. High-dimensionality in combination with large datasets can be extremely challenging. High-dimensional data are generally used over a wide range of fields such as biometric, e-commerce, and industrial applications. In order to use data characteristics, proper techniques and methods are needed to handle such high-dimensional data. Furthermore, data can have atypical characteristics and high-dimensional data structures, which means that conventional analysis techniques do not work well. To analyse extra useful information from high-dimensional data, novel approaches are required.

This special issue strives to provide a timely opportunity to discuss and summarize the latest developments in this area. The emphasis will be on the theoretical methodology and mathematical analysis, though applications concerning high-dimensional data, especially real datasets, are also welcome.

Therefore, contributions containing new ideas, new insights, and new applications are particularly welcome.

Potential topics include, but are not limited to:

• New methods, theory, and analysis of high-dimensional data
• New algorithms and applications
• Feature selection and analysis of high-dimensional data
• Clustering and recognition of high-dimensional data
• Computational intelligence related to Big Data
• Information technology related to industrial systems
• Hybrid methods and atypical datasets
• Informatics and biomedical engineering
• Medical signal analysis
• Information analysis with applications industry
• Real-world applications and other applications