Issues around global and personal security, healthcare for the 21st century, and optimisation of wireless communications drive our Information Engineering research.
Developing fundamental theory and applications relating to the generation, distribution, analysis and use of information in image and video, bioinformatics, health informatics, and optical and wireless communication.
The Information Engineering Research Group focuses on the development of computational models and algorithms, the analysis of signal, image and other data, and machine learning.
The Research Group is organised into five research laboratories:
Performs a wide range of image/video processing research with diverse application areas including video enhancement, scene reconstruction for 3D object modelling and autonomous vehicle navigation, gait recognition for human identification, action/activity recognition for video surveillance, and affective computing for emotion recognition via facial expressions, body language and EEG. Lead by Dr Tardi Tjahjadi and Dr Thomas Popham.
Focuses on applications of information engineering theory and methods to practical health problems, in which eHealth, healthcare technology and information communication technology can give significant contributions. The research covers chronic cardiovascular diseases (i.e., hypertension, congestive heart failure), wellbeing (e.g., mental stress detection), and accidental falls prediction. Lead by Dr Leandro Pecchia
Focuses on techniques to extract information out of omics datasets to enable improved predictive models and on how such information can be useful in synthesizing synthetic biological systems. Lead by Dr Vishwesh Kulkarni
Leads research in evolutionary optimisation of communication systems, wireless system design and analysis, energy harvesting techniques, wireless relaying and sensing, and cognitive radios. Lead by Dr Mark Leeson and Dr Yunfei Chen
Covers underwater optical communications to achieve high data rates and nanoscale communications to enable very small devices to form networks. Lead by Dr Mark Leeson