Two new Laureates for Melbourne

Two University of Melbourne researchers have received Australian Research Council (ARC) Laureate Fellowships to further their research into quantum imaging in biology, and stochastic modelling.

Melbourne’s Professor Lloyd Hollenberg (School of Phyiscs) and Professor Peter Taylor (Department of Mathematics and Statistics) were among 17 new Fellows recently announced by the Minister for Innovation, Industry, Science and Research, the Hon Senator Kim Carr at the University of Melbourne.

The Fellowships were funded as part of $47 million allocated by the Federal Government in grants to boost the nation’s research capabilities.

They, are the flagship awards of the Australian Research Council (ARC), designed to recognise and retain some of the very best researchers to work in this country, and to build ongoing research programs and teams of the highest quality.

Professor Hollenberg won the Fellowship for his research project entitled ‘New views of life: quantum imaging in biology.’ The Laureate program is expected to position Australia as an international leader in this emerging era of nano-scale quantum sensing and imaging in biology.

“In this research project we will create and apply new technology based on the quantum properties of diamonds, to address important problems in biology, from how cells differentiate at the beginning of life, to understanding brain function,” Professor Hollenberg says.

Professor Hollenberg observes that the convergence of the physical sciences, engineering and biology has been highlighted as one of the most significant themes of the 21st century, with the potential to create new technologies for the benefit of society.

His research project will establish multidisciplinary teams to forge a leading position in the application of emerging quantum-imaging technology to important problems in the life sciences. 

“We will apply imaging technology whose power derives from the rather non-intuitive quantum properties of fluorescent centres in diamonds to detect the minute magnetic fields associated with the basic functions of living cells and cellular networks in neuroscience,” Professor Hollenberg explains.

“This new detection and imaging capability may have important implications for nano-medicine, drug testing and understanding of brain function.”

Professor Taylor received the Laureate Fellowship for his project entitled ‘New Stochastic Models for Science, Economics, Social Science and Engineering’.

“Systems that are driven by stochastic, or random, effects are ubiquitous,” Professor Taylor says.

“It is crucial for society’s wellbeing, in economic and other terms, that we understand such stochastic systems, and learn to control and optimise their operation,” he explains.

The word ‘stochastic’ comes from the Greek ‘stokhastikos’, an adjectival form meaning ‘aimed at’ or ‘guessed’. Stochastic models are used to describe and understand the behaviour of systems that are subject to random variability, frequently over time or space, or both.

“At some level, almost every physical or man-made system is subject to stochastic effects,” Professor Taylor says.

“However, stochastic models are most appropriately used when large-scale randomness is an intrinsic property of a system.

“Sometimes we have a reason to create randomness deliberately, such as when we toss a coin to make a fair choice between alternatives, or when we design gambling games. In other cases, randomness can be an inherent property of the system under study.”

Professor Taylor gives the example of a checkout queue at a supermarket which he describes as a system driven by random effects: it is not known how many people will want to use the checkouts during a specified time period, or how many items that each customer will want to process.

“Systems that require stochastic modelling abound,” says Professor Taylor.

“In addition to gambling games and supermarket checkout queues, other examples are provided by virtual queues of calls waiting to be processed at a call centre, packet-flow processes in the Internet, and random social networks.

Stochastic models can also describe patients’ waiting times for elective surgery, the signal strength of a cellular phone network over a region in space, the variation in the number of individuals of an endangered species over time, the daily values of the All Ordinaries Index, and the times between floods of a given severity at a riverside town. 

“The range of examples across all areas of science, economics, social science and engineering is virtually limitless,” he says.

www.mro.unimelb.edu.au/