IEEE SIG on Big Data with Computational Intelligence

  • 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

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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

  1. Carlos Tavares Calafate, Technical University of Valencia, Spain
  2. Celimuge Wu, The University of Electro-Communications, Japan
  3. Chaoyang (Joe) Zhang, The University of Southern Mississippi, USA
  4. Chase Q. Wu, New Jersey Institute of Technology, USA
  5. Chau Yuen, Singapore University of Technology and Design, Singapore
  6. Cristian Borcea, New Jersey Institute of Technology, USA
  7. David Grace, University of York, UK
  8. Dazhao Cheng, University of North Carolina at Charlotte, USA
  9. Eryk Dutkiewicz, University of Technology Sydney, Australia
  10. Francisco J. Martinez, University of Zaragoza, Spain
  11. Fuqiang Liu, Tongji University, China
  12. Guanding Yu, Zhejiang University, China
  13. Guoliang Xue, Arizona State University, USA
  14. Honggang Zhang, Zhejiang University, China
  15. Jianwu Wang, University of Maryland, Baltimore County, USA
  16. Junaid Qadir, Information Technology University, Punjab, Pakistan
  17. Kok-Lim Alvin Yau, Sunway University, Malaysia
  18. Lin Zhang, Beijing University of Posts and Telecommunications, China
  19. Longzhi Yang, Northumbria University, UK
  20. Mehdi Bennis, University of Oulu, Finland
  21. Michelle Zhu, Montclair State University, USA
  22. Moustafa Youssef, Egypt-Japan University of Science and Technology, Egypt
  23. Paul Rayson, Lancaster University, UK
  24. Qiang Ni, Lancaster University, UK
  25. Senjuti Basu Roy, New Jersey Institute of Technology, USA
  26. Shiwen Mao, Auburn University, USA
  27. Sooksan Panichpapiboon, King Mongkut's Institute of Technology Ladkrabang, Thailand 
  28. Soufiene Djahel, Manchester Metropolitan University, UK
  29. Sye Loong Keoh, University of Glasgow, UK
  30. Tsutomu Yoshinaga, The University of Electro-Communications, Japan
  31. Vincent Poor, Princeton University, USA
  32. Wei Song, University of New Brunswick, Canada
  33. Xianfu Chen, VTT Technical Research Centre of Finland, Finland
  34. Xinzheng Niu, University of Electronic Science and Technology of China, China
  35. Yan Zhang, University of Oslo, Norway
  36. Yaochu Jin, University of Surrey, UK
  37. Yassine Hadjadj-Aoul, University of Rennes 1, France
  38. Yi Chen, New Jersey Institute of Technology, USA
  39. Yusheng Ji, National Institute of Informatics, Japan
  40. Zhu Han, University of Houston, USA
  41. Zizhong (Jeffrey) Chen, University of California, Riverside, USA