Special Research Initiatives - Grant ID: SR1101002
Funder
Australian Research Council
Funding Amount
$21,000,000.00
Summary
Stem Cells Australia. Despite progress in stem cell research, scientists do not understand how stem cells “decide” what to become. Stem Cells Australia will draw upon strengths within Australia’s premier stem cell research universities and institutes. This collaboration between leading bioengineering, nanotechnology, stem cell and advanced molecular analysis experts, will fast-track efforts to deliver a fundamental understanding of the mechanisms of stem cell regulation and differentiation, and ....Stem Cells Australia. Despite progress in stem cell research, scientists do not understand how stem cells “decide” what to become. Stem Cells Australia will draw upon strengths within Australia’s premier stem cell research universities and institutes. This collaboration between leading bioengineering, nanotechnology, stem cell and advanced molecular analysis experts, will fast-track efforts to deliver a fundamental understanding of the mechanisms of stem cell regulation and differentiation, and the ability to control and influence this process. Stem Cells Australia will deliver new methods for stem cell propagation and manipulation, new translational technologies for therapeutic applications, and will prepare Australia’s future stem cell scientific leaders.Read moreRead less
Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results ....Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results will test the generality of principles that have been developed in studies of female mate choice and extend these ideas to address intra-sexual selection operating through opponent assessment.Read moreRead less
Alpha-particles linked to recombinant antibodies targeting tumour cells have potential to effectively treat tumours while minimising normal tissue side effects. We will explore a novel alpha-particle therapy approach to solid tumours, by delivering 225Ac directly into tumour cells, or into cells that support the tumour (microenvironment). This approach will hopefully result in development of a new approach to treatment of cancers that are resistant to conventional therapies.
User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less
Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin ....Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
Development of methods and algorithms to support multidisciplinary optimisation. This project will aim to develop a number of novel and computationally efficient schemes to deal with the key challenges facing multidisciplinary optimisation. These advancements will allow us to solve a number of challenging and intractable problems in science and engineering.
Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected ....Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected outcomes include the
development of software that allows the solution of hitherto unsolved machine
learning problems, and the ability to solve problems larger than those solvable
by the current generation of machine learning tools.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101368
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Silicon 2.0: The nature of grown-in defects in very high-purity silicon. This project aims to produce technologies to maximise the electronic quality of silicon and mitigate the negative impacts of defects on high-efficiency solar cells. The intended outcomes are the development of novel solar cell processes to produce defect-free silicon and new characterisation techniques to image defects in silicon wafers. This would allow high efficiency solar cells to overcome their current limits and unloc ....Silicon 2.0: The nature of grown-in defects in very high-purity silicon. This project aims to produce technologies to maximise the electronic quality of silicon and mitigate the negative impacts of defects on high-efficiency solar cells. The intended outcomes are the development of novel solar cell processes to produce defect-free silicon and new characterisation techniques to image defects in silicon wafers. This would allow high efficiency solar cells to overcome their current limits and unlock the potential of current processes to produce solar cells with efficiency above 26 per cent, providing more efficient and affordable solar electricity.Read moreRead less
Nanophotonics for strong absorption in extremely thin solar cells: moving beyond silicon. This project will lead to the development of extremely thin solar cells made of novel low-cost materials, which would likely reduce the cost of photovoltaic technology. If the cost of photovoltaics was sufficiently low then it could have a major impact on reducing greenhouse gas emissions and pollution in Australia and worldwide.