Officers
Chair: Xianfu Chen, VTT Technical Research Centre of Finland, Finland, Email: xianfu.chen@vtt.fi
Vice-Chair: Chase Q. Wu, New Jersey Institute of Technology, USA, Email: chase.wu@njit.edu
Vice-Chair: Qiang Ni, Lancaster University, UK, Email: q.ni@lancaster.ac.uk
Vice-Chair: Kok-Lim Alvin Yau, Sunway University, Malaysia, Email: koklimy@sunway.edu.my
Advisor: Guoliang Xue, Arizona State University, USA, Email: xue@asu.edu
Advisor: Yaochu Jin, University of Surrey, UK, Email: yaochu.jin@surrey.ac.uk
Advisor: Shiwen Mao, Auburn University, USA, Email: szm0001@auburn.edu
Advisor: Yusheng Ji, National Institute of Informatics, Japan, Email: kei@nii.ac.jp
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Past Officers (2017-2022)
Chair: Celimuge Wu, The University of Electro-Communications, Japan, Email: celimuge@uec.ac.jp
Vice-Chair: Xianfu Chen, VTT Technical Research Centre of Finland, Finland, Email: xianfu.chen@vtt.fi
Vice-Chair: Chase Q. Wu, New Jersey Institute of Technology, USA, Email: chase.wu@njit.edu
Vice-Chair: Qiang Ni, Lancaster University, UK, Email: q.ni@lancaster.ac.uk
Vice-Chair: Kok-Lim Alvin Yau, Sunway University, Malaysia, Email: koklimy@sunway.edu.my
Advisor: Guoliang Xue, Arizona State University, USA, Email: xue@asu.edu
Advisor: Yaochu Jin, University of Surrey, UK, Email: yaochu.jin@surrey.ac.uk
Advisor: Shiwen Mao, Auburn University, USA, Email: szm0001@auburn.edu
Advisor: Yusheng Ji, National Institute of Informatics, Japan, Email: kei@nii.ac.jp
Scope and Objectives
Nowadays, we are facing explosive data growth. These data come from diverse sources, including business, entertainment, education, healthcare and science, and can be highly dimensional, heterogeneous, complex, unstructured and unpredictable. The challenges in analyzing “big data” call for fundamental techniques and technologies. At the same time, the big data analysis has created new opportunities for industries and academia.
Computational intelligence (CI) enables agents (or decision makers), for example, the computers and the smart devices, to process and analyze the captured data computationally, and subsequently to identify and explain the underlying patterns of the data, as well as to efficiently learn the specific tasks. CI covers a broad range of nature-inspired, multidisciplinary and computational methodologies, such as fuzzy logic, artificial neural networks, evolutionary computing, learning theory, probabilistic methods, and so on. CI technologies are expected to provide efficient and powerful tools that scale well with data volume for big data analytics and process, while addressing the challenges brought by the massive amount of data.
In summary, this SIG will focus on the technical challenges and applications of CI in big data. We envision that the combination of big data with a large collection of CI algorithms will reach the level of true artificial intelligence. The areas of interests include, but are not limited to, the following:
Fuzzy logic for big data analysis
Artificial neural networks for big data analysis
Evolutionary computing for big data analysis
Learning theory for big data analysis
Probabilistic methods for big data analysis
Machine learning for big data analysis
Big data and computational intelligence for networking
Big data and computational intelligence for communications
Big data and computational intelligence for computing
Big data and computational intelligence for image processing
Big data and computational intelligence for pattern recognition
Big data and computational intelligence for natural language processing
Fuzzy-based models for big data
Evolutionary models for big data
Platform for big data and computational intelligence
Algorithm for big data preprocessing
Founding Members
Carlos Tavares Calafate, Technical University of Valencia, Spain
Celimuge Wu, The University of Electro-Communications, Japan
Chaoyang (Joe) Zhang, The University of Southern Mississippi, USA
Chase Q. Wu, New Jersey Institute of Technology, USA
Chau Yuen, Singapore University of Technology and Design, Singapore
Cristian Borcea, New Jersey Institute of Technology, USA
David Grace, University of York, UK
Dazhao Cheng, University of North Carolina at Charlotte, USA
Eryk Dutkiewicz, University of Technology Sydney, Australia
Floriano De Rango, University of Calabria, Italy
Francisco J. Martinez, University of Zaragoza, Spain
Fuqiang Liu, Tongji University, China
Guanding Yu, Zhejiang University, China
Guoliang Xue, Arizona State University, USA
Honggang Zhang, Zhejiang University, China
Jianwu Wang, University of Maryland, Baltimore County, USA
Junaid Qadir, Information Technology University, Punjab, Pakistan
Kok-Lim Alvin Yau, Sunway University, Malaysia
Lin Zhang, Beijing University of Posts and Telecommunications, China
Longzhi Yang, Northumbria University, UK
Mehdi Bennis, University of Oulu, Finland
Michelle Zhu, Montclair State University, USA
Moustafa Youssef, Egypt-Japan University of Science and Technology, Egypt
Paul Rayson, Lancaster University, UK
Qiang Ni, Lancaster University, UK
Senjuti Basu Roy, New Jersey Institute of Technology, USA
Shiwen Mao, Auburn University, USA
Sooksan Panichpapiboon, King Mongkut's Institute of Technology Ladkrabang, Thailand
Soufiene Djahel, Manchester Metropolitan University, UK
Sye Loong Keoh, University of Glasgow, UK
Tsutomu Yoshinaga, The University of Electro-Communications, Japan
Vincent Poor, Princeton University, USA
Wei Song, University of New Brunswick, Canada
Xianfu Chen, VTT Technical Research Centre of Finland, Finland
Xinzheng Niu, University of Electronic Science and Technology of China, China
Yan Zhang, University of Oslo, Norway
Yaochu Jin, University of Surrey, UK
Yassine Hadjadj-Aoul, University of Rennes 1, France
Yi Chen, New Jersey Institute of Technology, USA
Yusheng Ji, National Institute of Informatics, Japan
Zhu Han, University of Houston, USA
Zizhong (Jeffrey) Chen, University of California, Riverside, USA