Optimisation & intelligent control
Model predictive control, metaheuristics, and hybrid methods for nonlinear, constrained, and multi-objective systems — robotics, scheduling, and resource allocation under uncertainty.
Focus areas
Research pillars
Interdisciplinary work spanning learning, control, optimisation, and deployment-conscious engineering.
Research
Applied machine learning & LLMs
Deep learning for forecasting and anomaly detection; language-model approaches for structured triage and decision support, with emphasis on validation and governance.
Energy, tariffs & infrastructure AI
Microgrids and renewable integration; optimisation of energy prices and tariffs; smart energy modelling linking simulation, control, and learning.
Trustworthy & secure computing
Security-relevant ML, ethical AI assessment as a global IEEE ethics assessor (IEEE Global AI Ethics Assessor programme), and governance-aware design for high-stakes environments.