We design new techniques and algorithms for wireless communications systems to increase spectral efficiency, reduce energy consumption and minimise latency. Applications include 5G and sensor networks.
Cybersecurity and coding
We study security and reliability in emerging communications networks exploiting the interplay between systems theory and error control coding. This is an important topic in the context of the Internet of Things as wireless communication between devices is extremely prone to malicious attacks.
Network design and optimisation
We design optimal interconnection networks using mathematical tools from combinatorics, computational geometry and variational calculus. Applications include underground mine planning, relay placement in wireless sensor networks, and physical microchip design.
Network estimation and control
Merging ideas from information theory, signal processing and control theory we take a new look at estimation and control problems in situations where communication links are imperfect. This area is highly relevant to Industry 4.0: cyber-physical systems, the Internet-of-Things and cloud computing.
Distributed systems, game theory and machine learning
There is a growing need to manage the efficiency and security of complex networked systems, which are no longer operated by a single agent, but require the coordination of many agents who manage different parts of the network. Game theory provides an excellent analytical framework to model such multi-agent problems in networks. However, traditional game-theoretic formulations suffer from scalability issues when there are large numbers of agents and complex, non-linear, non-convex system representations. Our research aims to improve the efficiency, scalability, and reliability of multi-agent decisions by integrating machine learning with game and system-theoretic methods in data-intensive network applications.
We use conventional communication theory and techniques to study and design systems that use chemical molecules to transmit information. We aim to understand biological systems from the aspects of signal processing and information theory, interface with biological systems, and gain the inspiration for the design of synthetic biological networks. Ultimately, our research will be used to help develop applications that use molecules to propagate signals, such as disease detection, drug delivery, and environmental monitoring.