Foundations and Architectures for Agent Systems. Computer systems are now involved in many aspects of everyday life, commerce, and industry. Making these systems more intelligent has thus become a priority research issue. Agents systems, with their emphasis on autonomy, proactiveness, reactivity, and sociability, are widely regarded as a crucial technology for realising the capabilities that computer systems will need over the next few decades. The proposed research aims to make some fundamenta ....Foundations and Architectures for Agent Systems. Computer systems are now involved in many aspects of everyday life, commerce, and industry. Making these systems more intelligent has thus become a priority research issue. Agents systems, with their emphasis on autonomy, proactiveness, reactivity, and sociability, are widely regarded as a crucial technology for realising the capabilities that computer systems will need over the next few decades. The proposed research aims to make some fundamental contributions to agent systems that will be used to build future computer systems that will have an even more profound positive impact on everyday life, commerce and industry than existing systems.Read moreRead less
Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, rec ....Network Intrusion Detection via Machine Learning. Computer security is an increasingly important, yet complex task. It
takes significant skills to configure systems properly such that they
are safe from malicious attacks.
The proposed project aims at designing automatic systems which are
able to adapt to an existing network configuration and which detect
novel and unusual events. For this purpose we will use modern machine
learning techniques, mainly based on kernels. In particular, recently
developed algorithms to estimate the support of a distribution and
detect rare events will be employed in this context.
The project is in cooperation with Dr. Ralf Herbrich (Microsoft
Research, Cambridge).
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Design surface feature recognition for near net shaped manufactured components. The aim of this project is to investigate methods and techniques that, given an ab initio design requirement, allow databases of knowledge from previous designs to be intelligently searched for similar patterns, both geometric and physical state, that will assess the likelihood of a successful design and suggest potential alternatives based on previous experience
The plan is to approach the research problem from a m ....Design surface feature recognition for near net shaped manufactured components. The aim of this project is to investigate methods and techniques that, given an ab initio design requirement, allow databases of knowledge from previous designs to be intelligently searched for similar patterns, both geometric and physical state, that will assess the likelihood of a successful design and suggest potential alternatives based on previous experience
The plan is to approach the research problem from a machine learning/pattern recognition point of view. By mapping the characterized properties into a search space of reduced dimensionality in which feature patterns have been pre-classified through supervised training, it should be possible to identify similar features.
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Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, ....Computer Vision Optimization Problems Using Machine Learning. Computer Vision concerns itself with understanding the world through the analysis of images obtained by a video or still camera. An important application is tracking of people in video and modelling their movements. This has evident applications in security, sport and entertainment. By enabling the computer to capture the motion of a subject in a video, we may detect suspicious activity in security, analyze the motion (golf-swing, diving style) of a sports-person, or capture the motion of an actor for animation or game applications. Development of a reliable technology requires new optimization techniques, which will place Australia at the forefront of the application of such research, commercially and for the public benefit.Read moreRead less
Creating the social genome: Advanced techniques for linking dynamic data. This project aims to develop novel efficient and effective models and techniques that enable record linkage of large dynamic databases while preserving the privacy of sensitive personal data. Social genomes are the digital footprints of our society. They are the basis of population informatics, which is revolutionising how researchers in various domains conduct studies, governments plan services and expenditures, and busin ....Creating the social genome: Advanced techniques for linking dynamic data. This project aims to develop novel efficient and effective models and techniques that enable record linkage of large dynamic databases while preserving the privacy of sensitive personal data. Social genomes are the digital footprints of our society. They are the basis of population informatics, which is revolutionising how researchers in various domains conduct studies, governments plan services and expenditures, and businesses advertise and interact with their customers. A core requirement of population informatics is the linking of large dynamic databases that contain details about people from diverse sources. The expected outcomes of this project will provide novel solutions to the challenges of population informatics faced by Australian organisations.Read moreRead less
Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision m ....Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision making. The project will revolutionise the design of information services where computers deal with humans and location in time-critical or stressful situations, including emergency calls, disaster response and local search queries. The uptake of this design by industry will lead to economic benefits as well as a safer society living in a smarter environment.Read moreRead less
Advancing future primary teachers' engagement in science inquiry learning. Australia's challenges in regard to scientific literacy and growth of student enrolments in science need to be addressed at multiple levels, starting with the preparation of future primary teachers. Promoting children's early interest in inquiry-based science is essential, yet a challenge for many teachers. This project examines the complex and dynamic interplay of cognitive, metacognitive and emotional processes in futur ....Advancing future primary teachers' engagement in science inquiry learning. Australia's challenges in regard to scientific literacy and growth of student enrolments in science need to be addressed at multiple levels, starting with the preparation of future primary teachers. Promoting children's early interest in inquiry-based science is essential, yet a challenge for many teachers. This project examines the complex and dynamic interplay of cognitive, metacognitive and emotional processes in future primary teachers' engagement in collaborative inquiry-based science activities. A comprehensive intervention based on these insights aims to determine how scaffolding productive engagement can improve the quality of primary teachers' preparation for inquiry-based science.Read moreRead less
Individual Differences in Orientations to Risk and Uncertainty. The main goal of this research project is to extend and integrate three individual-differences approaches to predicting and explaining human judgement and decision making (JDM) and risk-taking behaviours (RTB) under uncertainty: Cognitive-capacity, preferences and dispositions, and dual cognitive process approaches. It will achieve this by studying the joint impact of cognitive style, capacities, and RTB/JDM dispositions on performa ....Individual Differences in Orientations to Risk and Uncertainty. The main goal of this research project is to extend and integrate three individual-differences approaches to predicting and explaining human judgement and decision making (JDM) and risk-taking behaviours (RTB) under uncertainty: Cognitive-capacity, preferences and dispositions, and dual cognitive process approaches. It will achieve this by studying the joint impact of cognitive style, capacities, and RTB/JDM dispositions on performance in appropriate JDM tasks. JDM and RTB are at the root of managing uncertainty, human adaptiveness and rationality. This project will also extend our knowledge of gender differences in JDM and RTB, and lay foundations for systematic cross-cultural studies on this topic.Read moreRead less
Face recognition: Properties and origins of whole-face processing. Humans identify other individuals almost entirely by their faces. Correspondingly, research has demonstrated a "special" style of cognitive processing that is unique to faces (at least in ordinary adults). The present project will address two major theoretical issues: (1) the exact nature of the special processing for faces, and (2) the extent to which it is innate, or learned. New progress in understanding these issues will be m ....Face recognition: Properties and origins of whole-face processing. Humans identify other individuals almost entirely by their faces. Correspondingly, research has demonstrated a "special" style of cognitive processing that is unique to faces (at least in ordinary adults). The present project will address two major theoretical issues: (1) the exact nature of the special processing for faces, and (2) the extent to which it is innate, or learned. New progress in understanding these issues will be made using a series of novel experimental techniques. These techniques isolate the specific contribution of the face recognition system, independent of contributions from object recognition, and from early visual processing.Read moreRead less
Special cognitive processing for faces: Expertise effects, and links to neural mechanisms. Humans identify other individuals primarily by their faces. Evidence from cognitive psychology indicates a special 'whole-face' (as opposed to part-based) style of processing for upright faces. This project will provide new insights into two long-standing issues about the origin of special face processing: (1) whether it derives from generic expert recognition processes or has some face-specific innate co ....Special cognitive processing for faces: Expertise effects, and links to neural mechanisms. Humans identify other individuals primarily by their faces. Evidence from cognitive psychology indicates a special 'whole-face' (as opposed to part-based) style of processing for upright faces. This project will provide new insights into two long-standing issues about the origin of special face processing: (1) whether it derives from generic expert recognition processes or has some face-specific innate component; and (2) the extent to which it can be distinguished from part-based processing at the neural level using both functional brain imaging (fMRI) and adaptation to distorted faces.Read moreRead less