Organization profile

Profile Information

The Machine Intelligence group conducts cutting-edge research in the areas of artificial intelligence, web science, machine learning, computational biology, digital computer games and computer networks.

Much of the group’s research provides intelligent techniques to design systems that: 1) support decision making of human/machine operators interacting with others under uncertainty; 2) analyze large scale of data to provide online prediction and personal recommendations; 3) mine text for knowledge through information extraction and other natural language processing; 4) develop mathematical models to predict and interpret biological and biomedical functionalities and 5) apply machine learning to wireless network and security problems. The group focuses on real-world applications in computer games, robot navigation, social media, biomedical informatics and networks. Recently the group extends its research antenna into big data research and application and the focus is on the use of artificial intelligence based technologies to support actional data mining, data visualization, user modeling and so on.

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    Projects

    Research Output

    Team Recommendation Using Order-based Fuzzy Integral and NSGA-II in StarCraft

    Wang, L., Zeng, Y., Chen, B., Pan, Y. & Cao, L., 18 Mar 2020, (Accepted/In press) In : IEEE Access. 1, 12, p. 1-13 13 p.

    Research output: Contribution to journalArticle

    Open Access
    File
  • A Data-driven Approach to Solve a Production Constrained Build-order Optimization Problem

    Wang, P., Zeng, Y., Chen, B. & Cao, L., 17 Oct 2019, Proceedings of the 38th Chinese Control Conference. IEEE, p. 2692-2697 (Chinese Control Conference (CCC); vol. 2019).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
    File
  • 62 Downloads (Pure)

    A Heterogeneous Multiattribute Group Decision-Making Method Based on Intuitionistic Triangular Fuzzy Information

    Xu, J., Dong, J., Wan, S., Yang, D. & Zeng, Y., 7 Aug 2019, In : Complexity. 2019, 18 p., 9846582.

    Research output: Contribution to journalArticle

    Open Access
    File
  • 170 Downloads (Pure)

    Press / Media

    University awarded prestigious grant to investigate the AI race

    The Anh Han

    9/10/18

    1 Media contribution

    Press/Media: Press / Media