Our goals

Climate Change is one of the largest issues facing us today, and one which particularly immobilises youth. It is crucial to have robust climate models in order to be sure of what is happening, and to predict the future. These involve the collaboration of mathematicians, statisticians and physicists.  

Food security and energy future capacity are major issues. Development of clean energy and efficient forms of energy storage and transfer are already a major research area for the Centre for Clean Energy Technology (CCET) and other members of the School. The security of our future food production requires models of the disease profile, a collaboration between mathematicians and chemists, and the development of suitable risk profiles to develop insurance instruments for crops. The emergence of antibiotic resistant bacteria which attack crops and livestock is a further area where biochemistry and environmental chemistry intersect.

The School strives to continue development of capabilities in all of these areas.

The impact of a growing population with an ever-ageing profile is an issue for Australia. Our School is involved in the 45-up project, which uses statistical tools to analyse health issue for ageing Australians. Our statisticians will also continue to be involved in the Digital Health CRC, which has the aim of using big data tools in medical diagnostics. An ageing population also represents a major economic issue for Australia in the area of provision of superannuation and pensions. Currently, members of the Quantitative Finance Research Centre (QFRC) are working to find solutions for this.

The emergence of 'superbugs' is a matter of extreme concern, and our biochemists are working to identify methods for dealing with this threat. The Institute for Biomedical Materials and Devices (IBMD) is using nanotechnology in medical science, creating nano-particles which can help in the identification of individual cancer cells, and the introduction of simple hand-held devices to exploit this technology. Their work is a deep collaboration between fundamental physics and biology.

An issue for science of the future is the increase in and availability of human genome data.  In the new age of personalised genomic medicine, how is genetic data obtained, who has access to it and under what circumstances?  Related, is the issue of DNA security as nations and corporations seek to build records of the DNA of members of the population. Who, if anyone, should be included? How should the records be protected? This requires biological, mathematical and statistical models as well as information technology. Genetic engineering of the human genome is currently bound up with ethical issues but is increasingly seen as a potential health intervention. What will be the effect of localised genetic changes on the complex biological system that is the human body?

The School is to be one of the top few forensic science schools in the world. The Centre for Forensic Science (CFS) has breadth and depth of expertise in the use of science, technology and logical inferences to address questions relevant to policing, justice and security. Areas of strength include fingerprint analysis, micro-traces (e.g. gunshot residue), forensic genetics, with developing new expertise in digital forensic science. There are strong links with statistics via Bayesian methods in evidence and crime statistics. New perspectives on forensic science come from its interpretation as the study of traces left by human and other activity. These often link to social dimensions or disciplines like criminology, ethics, behavioural sciences and law. The CFS hosts the AFTER facility for research in taphonomy, unique in the Southern Hemisphere. Continuation and further development of the CFS are critical to the School’s mission.

The School will play an important role both in the development of new techniques and ideas in artificial intelligence and data science and in using this new science for the technological transformation which society is undergoing. We have researchers working on fast Bayesian methods, AI methods in climate science, large data sets for astronomical data, complexity theory, stochastic methods, forensic statistics, financial and market analysis, health statistics and forensic genetics. Taken together these proved an unparalleled depth of expertise in the area colloquially known as 'big data'. In bringing these experts together from different fields, we will contribute to the building of a new phase in the data revolution, where modern mathematical and statistical methods are introduced and where the users of the new algorithms become involved in their refinement and development. This will involve a critical and deep interaction with data scientists in the Faculty of Engineering and IT (FEIT).

Some of the crucial areas for the future which we will contribute to are: data security and privacy, data overload, data analytics, geometric and topological data analysis, use of data in sustainability research, use of large data sets in health science, use of data in financial and economic modelling, use of data in social sciences and legal applications, and bioinformatics.

Much of the future of our society depends on the development of new technologies. Initially seen as 'blue skies' research, these are the areas which will transform our capability and adaptability in the decades to come.  

Quantum technology is one of the drivers for change. The fundamental processes of nature are being exploited to develop previously undreamt of computing power: in a collaboration across the Sydney basin, and at UTS spanning across Science and FEIT, we will study the quantum mechanics of interactions of photons at low temperatures and how this impacts on quantum computing. The theory of quantum electrodynamics governs the interactions between elementary particles (photons, electrons) and is being studied in this investigation.

New methods of computational physics and computational chemistry will lead to understanding of plasmonics and behaviour of nano-particles, and how particles interact with the surfaces of materials. This can lead to new imaging techniques, new biomaterials for medical science, new wifi technologies and many other potential applications.

Stochastic modelling is the mathematics of randomness, and is in increasing use for a range of applications. But much of the theory is not sufficiently refined for applications: the whole intersection with data analysis is not well understood; the relationship between stochastics and statistics and data assimilation is based on assumptions which are often not satisfied in practice; we do not know how to optimise under uncertainty. Complex biological systems will require new models which take into account myriad biochemical and biomolecular interactions.  This area lies between pure mathematics, applied mathematics, probability and statistics and is one where the School will make a substantial contribution. Artificial Intelligence is increasingly important, and opportunities to contribute to its development will be actively sought out.