RoboCrab: An integrative approach to the natural ecology of decision making. The project aims to analyse and model the sophisticated and context-dependent escape behaviour of fiddler crabs under both natural conditions and in controlled laboratory settings. A crucial problem for biology is to understand how animals can make adaptive decisions in natural, complex sensory environments; such understanding also has direct application to robotics. The project plans to examine the effects of eye stabi ....RoboCrab: An integrative approach to the natural ecology of decision making. The project aims to analyse and model the sophisticated and context-dependent escape behaviour of fiddler crabs under both natural conditions and in controlled laboratory settings. A crucial problem for biology is to understand how animals can make adaptive decisions in natural, complex sensory environments; such understanding also has direct application to robotics. The project plans to examine the effects of eye stabilisation and oscillation, record from key neural stages using naturalistic stimuli to derive precise algorithms, and integrate and test the results on a robot model – RoboCrab. This may provide new insight into the integration of low-level sensory input with behavioural decision making circuits and the evolution of escape behaviours.Read moreRead less
Mid-Career Industry Fellowships - Grant ID: IM230100042
Funder
Australian Research Council
Funding Amount
$980,358.00
Summary
Unlocking the full reproductive potential for hybrid wheat breeding. Globally, wheat is cultivated as an inbred self-fertile crop with yield gains stagnating over the last decades. This contrasts with unabated yield gains and yield stability achieved for rice and corn through hybrid breeding and cross-pollination. Wheat hybrids hold potential for a 10-22% yield boost, but commercial deployment is restricted due to high seed production costs, a result of wheat’s floral architecture and poor outcr ....Unlocking the full reproductive potential for hybrid wheat breeding. Globally, wheat is cultivated as an inbred self-fertile crop with yield gains stagnating over the last decades. This contrasts with unabated yield gains and yield stability achieved for rice and corn through hybrid breeding and cross-pollination. Wheat hybrids hold potential for a 10-22% yield boost, but commercial deployment is restricted due to high seed production costs, a result of wheat’s floral architecture and poor outcrossing characteristics. This project aims to reduce costs by improving wheat’s female receptivity to airborne pollen, a major bottleneck to commercial realization of hybrids globally. Higher and more stable yields from wheat hybrids will ensure food security in the face of climate uncertainty and growing population.Read moreRead less
The Importance Of Neutrophil Plasticity In Early Cystic Fibrosis Lung Disease
Funder
National Health and Medical Research Council
Funding Amount
$318,768.00
Summary
Lung disease is a lifelong problem for people with cystic fibrosis (CF). Blood immune cells called neutrophils swarm the lung and cause ongoing damage. No treatments exist because how CF lungs talk to neutrophils is poorly understood. I will apply new skills from an international neutrophil expert to study samples from AREST CF, a world leading CF research group. This unique combination will recreate the early CF lung in the laboratory, testing triggers of CF lung disease and potential drugs.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Epithelial Drivers Of Neutrophil Plasticity In Early Cystic Fibrosis Lung Disease
Funder
National Health and Medical Research Council
Funding Amount
$849,462.00
Summary
Why airway inflammation becomes chronic so early in life for people with cystic fibrosis (CF) is unclear. This project will use the latest techniques to characterise immune cells found in airways of infants with CF and model in the laboratory how immune cells react to the CF airway. We will challenge CF airway cells with different bugs that can infect the lung, then see if the responses by CF airway cells can change the normal response of immune cells, triggering chronic disease.
Using Systems Biology To Understand Asthma Exacerbations And Develop Better Treatments
Funder
National Health and Medical Research Council
Funding Amount
$791,734.00
Summary
Our research using cutting-edge technology has demonstrated that not all asthma attacks are the same. There are two major subtypes of asthma attacks. Currently, we use the same medication to treat all asthma attacks, and this medication targets the symptoms rather than the cause. This research will conduct detailed laboratory studies to understand what causes the two different types of asthma attacks, and test new treatments that are targeted and tailored to each type of asthma attack.
Antigen Presentation, Recognition And The Immune Response
Funder
National Health and Medical Research Council
Funding Amount
$15,780,848.00
Summary
This program focuses on understanding the development of immune response to viruses and other infectious agents using a broad array of techniques to dissect the function of various immune cell types and to explore the relationship between structure and function of important cell surface molecules. These studies will improve our ability to design new generation vaccines for combating infectious diseases, controlling cancer, or limiting autoimmune diseases like diabetes.
Arbovirus Activation And Modulation Of NLRP3 Inflammasome
Funder
National Health and Medical Research Council
Funding Amount
$779,720.00
Summary
This project aims to establish how mosquito borne viruses such as Ross River and dengue viruses interacts with the human host to cause disease, including how the virus evades the host’s immune response to persist and cause disease for prolonged periods. Knowing how differences in the virus and the host’s immune system interplay to cause asymptomatic to severely disabling disease will assist in devising new treatments and prevention programs to lessen the impact of these diseases in Australia.
A specialised set of T lymphocytes called Mucosal Associated Invariant T (MAIT) cells react against bacteria and yeast, and reside at mucosal sites where the body's immune defences are most easily breached, e.g. respiratory tract and intestinal mucosa. This study investigates the role of MAIT cells in both protection and pathology in bacterial infections. Controlling MAIT cells could help in treating these conditions.
Tools, methodologies and reasoning support for developing companion-toy modules. This project investigates building of modules for an intelligent Toy which can be customised and adapted over time by add-on modules. Intelligent interactive toys are growing in popularity, and the ability for such a toy to develop over a prolonged lifetime, is both a sound business idea and a mechanism for extending the useful life of the Toy.