Current Research Interests
- Adversarial and distributed machine learning
- Networked system cyber and cyber-physical security
- Machine and deep learning applications to engineering
- Applications of distributed optimisation and game theory to IoT and Cyber-Physical Systems (CPS)
- Electrical power systems: smart grid, renewables, electricity markets
- Wireless, Cognitive, and Software-Defined Wireless Networks
Research Questions
The fundamental question I aim to address with my research is:
“How do we create more efficient, incentive-aligned, and secure systems?"
Towards this overarching goal, I work on these specific sub-problems:
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How can we analyse and design systems where multiple participants (as independent decision makers with personal preferences) interact with each other?
Applications: IoT/CPS, power systems, wireless communications.
Methods: game theory, distributed optimisation, mechanism design, machine learning -
How do we better integrate modern computing and machine learning to engineering systems (control, communication, signal processing)?
Applications: IoT/CPS, power systems, wireless communications.
Methods: machine/deep learning, distributed optimisation, control, communications, signal processing. -
How can we make security decisions and manage risks in complex systems in a principled, quantitative, and analytical manner?
Applications: IoT/CPS, critical infrastructure, defence.
Methods: game theory, quantitative risk models, machine learning -
Can we develop a better understanding of Deep Learning?
Applications: IoT/CPS, control, communications
Methods: information theory, optimisation, source coding