Major research areas
Data analytics and machine learning
High-performance data mining
Mining data, recognising patterns, big data dimensionality reduction and visualisation, clustering and classifying data, modelling interactions and causality to better understand systems and behaviours
Computational diagnostics for intelligent health care
Using advanced methods for non-linear and dynamical signal processing and time series analysis for data-driven modelling of human behaviour, processes of sleep, cardio-respiration, diabetes, mental health, age-related conditions.
Modelling complex systems
Developing advanced mathematical and computational models based on dynamical systems and differential equations, with applications to physiology, health, medicine and defence.
Using and developing complex models, algorithms and machine learning-driven knowledge system development and management to make accurate predictions and obtain meaningful insights from data. Investigating and developing approaches to ensure AI systems behaviour remains beneficial to humanity.
Providing efficient algorithms for recognising objects, text, handwriting, images and videos, with advance noise filtering and image reduction techniques in security and intelligent processes.
Aiming to leverage information about the context of acquisition and the image formation process to develop methods, algorithms and techniques for processing visual and multimodal data, requiring the least amount of user intervention possible.
Discrete and continuous optimisation
Providing solutions to large-scale complex problems, such as timetabling, resource allocation, scheduling in the manufacturing industry, facility location planning and supply chain and logistics.
Decision sciences and fuzzy systems
Advanced multicriteria decision-making methods based on cooperative games, non-linear integrals and fuzzy systems.
Graph theory and discrete geometry
Smart city-based traffic network
Developing index techniques and algorithms to manage traffic network data and supporting advanced city planning and scheduling in complex scenarios.
Smart e-business-driven social network
Developing novel social computing models and algorithms for innovating the online advertisement strategies and tracking the evolving changes in social media trends.
Smart biotechnology information network
Designing the AI-powered modern database system to build the bio-information knowledge graph and innovate the lifecycle of health ecosystems.
Data Analytics Lab
The Data Analytics Lab is conducting internationally recognised research to discover data patterns, properties of data and model complex systems. We build data-driven models and intelligent algorithms to solve fundamental and industrial real-world problems.
The Mathematics Lab brings together mathematicians and data scientists within the School of Information Technology, consolidating theoretical and practical research in decision sciences, computational mathematics and optimisation, applied statistics and mathematical modelling.
Smart Networks Lab
The Smart Networks Lab is designed to deliver world-leading research and emerging technologies by solving the practical problems in complex network data systems and structured data systems. It provides a real-time systematic solution to address the challenging tasks in the full process of data collection, data maintenance, data analytics and decision-making.
Machine Intelligence Lab
The Machine Intelligence Lab conducts world-class research to harness the transition from a process-defined world to a data-driven one by creating and developing future AI technologies and techniques that will have transformational effects across the economy and society. We aim to design intelligent algorithms that automate problems of data analysis, planning and decision-making. The lab pursues interdisciplinary research within the areas of pattern analysis, machine learning and AI, aimed at discovering the principles underlying the design, development and deployment of artificially intelligent systems.