Decision Science and Optimisation Group

The Decision Science and Optimisation Group focuses on advancing computational and analytical methodologies to enhance decision-making, predictive modelling, and optimization across diverse industries. The group specializes in Decision Support Systems (DSS), Mathematical Modelling, Operations Research (OR), and Artificial Intelligence (AI) integrating cutting-edge techniques from data science, artificial intelligence, and high-performance computing to solve complex real-world challenges.

By developing intelligent decision-support frameworks, creating robust mathematical models, applying advanced optimisation strategies, and leveraging AI-driven analytics, the group addresses critical problems in logistics, finance, healthcare, manufacturing, and resource management. Its interdisciplinary approach combines theory and practical applications, ensuring innovative solutions that drive efficiency, sustainability, and strategic planning in dynamic environments.

Areas of Interest

Decision Support Systems (DSS)

Decision Support Systems (DSS) are computational tools designed to assist in complex decision-making by analysing vast datasets, applying machine learning algorithms, and generating actionable insights. DSS research focuses on developing interactive, AI-driven platforms that enhance strategic planning, risk assessment, and real-time decision-making in areas, like business intelligence, supply chain management, and policy formulation.

Mathematical Modelling

Mathematical modelling involves the development of abstract representations of real-world systems using mathematical structures and equations. Researchers in this field apply deterministic and stochastic models to simulate, predict, and optimise processes in diverse domains, including epidemiology, environmental management, financial risk analysis, and engineering. By refining models through computational simulations and data-driven techniques, the group enhances problem-solving capabilities in complex and uncertain environments.

Operations Research (OR)

Operations Research applies mathematical, statistical, and computational techniques to optimise decision-making in complex systems. The group's OR research focuses on areas such as linear and nonlinear programming, simulation modelling, game theory, and network optimisation. These methodologies help in solving large-scale logistical, scheduling, and resource allocation problems in sectors like transportation, energy, healthcare, and telecommunications.

Artificial Intelligence (AI)

Artificial Intelligence (AI) research in the group focuses on developing machine learning, deep learning, and natural language processing (NLP) techniques to enhance predictive analytics, automation, and decision-making. Key areas of interest include AI-driven optimisation, intelligent automation, and sentiment analysis, where AI is used to assess public opinion, customer feedback, and emotional cues from text and speech data. By integrating AI with decision-support frameworks and mathematical modelling, researchers aim to create adaptive, data-driven solutions that improve efficiency, security, and user experience across industries such as finance, healthcare, marketing, and smart systems.

Through interdisciplinary collaboration and technological innovation, the Decision Science and Optimisation Group contributes to the development of smarter, more efficient systems that enhance decision-making, optimise resources, and drive scientific and industrial advancements.

Members: