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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.

Fingerprint Dive into the research topics where Machine Intelligence Research Group is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

Game theory Engineering & Materials Science
Genes Engineering & Materials Science
Genome Medicine & Life Sciences
Evolutionary Game Mathematics
Metabolism Engineering & Materials Science
Learning systems Engineering & Materials Science
Systems Biology Medicine & Life Sciences
Gene expression Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2018 2021

Research Output 2008 2019

91 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 journalArticleResearchpeer-review

Open Access
File
Triangular fuzzy number
Group decision making
Entropy
Geometry
Multiple objectives
78 Downloads (Pure)

A Learning Design Framework to Support Children with Learning Disabilities Incorporating Gamification Techniques

Shaban, A. & Pearson, E., 9 May 2019, CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems: Weaving The Threads of CHI. 3312806. (Conference on Human Factors in Computing Systems - Proceedings).

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

Open Access
File
learning disability
learning
deficit
management
education

Combining metabolic modelling with machine learning accurately predicts yeast growth rate

Culley, C., Vijayakumar, S., Zampieri, G. & Angione, C., Jun 2019, (Accepted/In press).

Research output: Contribution to conferencePaperResearchpeer-review

Open Access
File
Metabolic engineering
Gene expression
Yeast
Industrial applications
Learning systems

Press / Media

University awarded prestigious grant to investigate the AI race

The Anh Han

9/10/18

1 Media contribution

Press/Media: Press / Media