Honours topics
Half of your time as an honours student is spent working on a project. But first you have to find a project topic.
The "official" reference for projects proposed by potential supervisors is the CECS projects database.
There are projects there available for all levels of research, including short projects, summerscholarship projects, Honours projects, Masters and PhD projects. All potential research students at any level are urged to browse it.
If you see a project that looks interesting, email the potential supervisor about it. Don't be afraid to discuss possible variations to the listed project: what appears on the web site is generally more of a suggestion than a rigid specification.
You don't have to be constrained by what you see on the project website. If you have something that you would like to work on as a project, then feel free to discus it with the honours convener to see if it could form the basis of an honours project and to identify a possible supervisor. Look at the web pages of Computer Science staff to find out their research interests. Remember that projects may also be supervised by people outside the College, or even ontside the University: from CSIRO or NICTA, for instance.
Former Project Topics
For your interest, here is an archive of Honours project proposals from previous years. Some of them are quite ancient now, of course, but they may help to give you ideas of the kind of thing which is suitable.2009 Honours project proposals
Web Service Management System (WSMS)
Service Oriented Architecture (SOA) is an emerging computing paradigm, in which infrastructure, platforms and softwares are transformed into services that can be consumed by anyone, anywhere, anytime. The trend of SOA has become noticeable in recent years. An increasing number of infrastructure and software services have been available on the Web, such as Amazon EC2 and Google Doc. The WSMS project of CSIRO aim at building an integrated framework for managing Web services. In this framework, Web services are first class objects that can be queried, composed, trusted, and changed. This project will explore research issues pertaining to the whole Web service lifecycle. We expect the outcome to become driving technology for the future service paradigm.
In WSMS, we offer the following opportunities as Honours projects:
Web Services Query Language
Web services have been the main force in driving service-oriented computing that promises not only a new paradigm for B2B collaboration, but also an opportunity for the creation of value-added services and new businesses. We foresee that web services will be as popular as today's web pages in future. However, how to manage and apply the large number of web services for end-users in their daily life remains a big challenge. CSIRO ICT Centre is conducting a research project (WSMS: Web Services Management System) to address the above challenge. One of research efforts in this project is to allow end-users/applications to express their requirements in a query language so that WSMS can resolve the query with the underlying web services.
Goals for this project: In this project, we will design and implement a query language for automatic web services discovery and execution.
Requirements: Programming skills in Java or C/C++ is essential; knowledge and experiences with web services and compiler are preferred.
Student's gain: The student will learn how to design and implement a computer language from scratch. He/she will also gain experiences and skills in web services, ontology and XML. The outcomes of this project may be published in an international conference/journal, which would increase the student's research credibility.
Supervisor: Dr. Shiping Chen (shiping DOT chen AT csiro DOT au) and Dr. Xuan Zhou (xuan DOT zhou AT csiro DOT au)
Evolutionary Algorithms for Optimal Composition of Web services
Service composition is an important part of the life cycle of services innovation research. It is evidently seen by the fact that Web service composition has attracted an increasing attention recently. When the quality of Web services (QoWS) is concerned, the objective of Web service composition becomes to find an optimal solution of composition. It is an NP-hard problem. Different strategies have been proposed so far to make service composition easier, for example, Genetic Algorithms (GAs) and Multi-objective Genetic Algorithms, Integer Programming (IP) and Mixed Integer Programming (MIP), Constraint Programming, Particle swarm optimisation, Ant Colony optimisation, and so on. This study aims to investigate different evolutionary algorithms and related techniques for optimal composition of Web services.
Goals for this project: this project will implement a number of different evolutionary algorithms and a comparison of these algorithms will be examined thoroughly (based on the empirical dataset).
Requirements: Students need to be proficient with Java programming.
Student's gain: The student will gain a deep insight into the evolutionary algorithms and their applications in the field of Web services. The work will be carried out in a world-leading research group (CSIRO) and will be conducted within the leading academic research infrastructure. The results of this project will include a proof-of-concept prototype and an international journal publication.
Supervisor: Dr. Li Li (lily.li@csiro.au) and Dr. Dongxi Liu (dongxi.liu@csiro.au)
Context Sensitive Web Service Composition
Context is recognised as important and has been widely studied in the field of Mobile and Pervasive Computing. It needs to be explicitly described and managed in Web service composition so that different participating Web services can be connected correctly. As the context of a Web service changes as the state of a predefined environment evolves, hard-coding context into the application is insufficient. We argue that the following supports are necessary to develop a full workable service composition (engine): (1) Service composition infrastructure/middleware (to achieve context-awareness); (2) Context sensitive composition model and algorithms.
Goals for this project: this project will first develop a model and some algorithms. The proposed algorithms will be evaluated a real Web service environment (currently, this environment is running well within CSIRO Web service Theme).
Requirements: Students need to be proficient with Java programming. General knowledge of Service-oriented Computing is required.
Student's gain: The student will gain a deep insight into the evolutionary algorithms and their applications in the field of Web services. The work will be carried out in a world-leading research group (CSIRO) and will be conducted within the leading academic research infrastructure. The results of this project will include a working prototype and publications to be submitted to the international conferences or journals.
Supervisor: Dr. Dongxi Liu (dongxi.liu@csiro.au) and Dr. Li Li (lily.li@csiro.au)
Reputation-based Trust Management in Composite Web Services
With the introduction of Web Services and Semantic Web, the World Wide Web has evolved into a collection of hundreds and thousands of services deployed with an aim of providing a wide variety of services to general public. Examples of such services range from general information services like Wikipedia to specific business services like Amazon. As services proliferate on the Web, several services may provide same functionalities to a service consumer. In these situations, trust is one of the essential criteria a consumer can use in selecting the right set of services. Therefore, there is a need for a robust trust management system that utilizes the perception-based knowledge of the communities in the Web. In order to develop such a system, we are investigating a mechanism of providing a robust trust model for web services. Our model is based on the reputation of services as rated by service consumers in the Web communities. This project aims to investigate a mechanism of managing reputation-based trust in composite services, i.e. services composed of a set of services.
Goals for this project: In this project, we will design, implement and deploy a distributed reputation-based trust management model for composite services.
Requirements: The student should have good knowledge and experience with Java programming. Knowledge of Web Services is desirable but not mandatory.
Student's gain: The project provides an opportunity for the student to contribute to an emerging area in computer science: Web Services and Service Computing. The work will be carried out in a research group of CSIRO and the student will have an opportunity to gain insight into R&D in both industry and academia. The project outcome will include a working prototype that can be demonstrated in an international conference and possibly a publication in an academic journal.
Supervisor: Dr. Wanita Sherchan (wanita DOT sherchan AT csiro DOT au) and Dr. Surya Nepal (surya DOT nepal AT csiro DOT au)
Change Management for Composite Web Services
This project aims at developing a bottom-up change management architecture for composite service and design a change management model which can capture the triggering changes of the outsourced Web services and propagate the change to composite service and generate reactive changes at the service schema level. The work will include a taxonomy or specification of bottom-up changes in an SOE (Service Oriented Enterprise) context which include triggering changes and reactive changes. For each type of change, a list of functional and non-functional changes will be defined. An appropriate model will be proposed to model these changes. Some mappings rules can be defined to map between different levels of changes. Automatic change management algorithms will be proposed to capture and manage the bottom-up changes. Finally, some evaluation will be carried on to assess the bottom-up change management system.
Goals for this project: The goal is to design a bottom-up change management architecture for composite services.
Requirements: Students will need to be proficient systems programmers with good C++ or Java skills.
Student's gain: The student will work on an interesting research problem with potential impact on Web services. The work will be carried in a research group of CSIRO. The student will get an insight of the R&D in both industry and academia. The results will include a working prototype that can be demonstrated in an international conference and a publication in an academic journal.
Supervisor: Dr. Jemma Wu (jemma DOT wu AT csiro DOT au)
Web Service Optimization
When selecting services on the Web, a user is usually faced with too many choices. For instance, both Yahoo and Google provide map services, characterized by different features. The user needs to pick one that can best satisfy her needs. This project aims at developing a system for helping user make the best selection among thousands of Web services. We will apply the technologies in decision making and artificial intelligence to support our solution.
Goals for this project: The goal is to design a Web based service selection system.
Requirements: Students need to be proficient will C++ or Java programming.
Student's gain: The student will work on an interesting research problem with potential impact on Web services. The work will be carried in a research group of CSIRO. The student will get an insight of the R&D in both industry and academia. The results will include a working prototype that can be demonstrated in an international conference and a publication in an academic journal.
Supervisor: Dr. Xuan Zhou(jxuan DOT zhou AT csiro DOT au)
Efficient network monitoring and routing via FPGAs
Research area: software engineering, networking, formal languages, HW/SW design
Difficulty: high
Supervisor: Bob Edwards (DCS), Dr. Andreas Bauer (RSISE & NICTA)
Background:
The network code of modern operating systems is very involved as it allows users to configure the entire routing either to protect themselves from dangers in the Internet, or to set up their own networks and to control which traffic goes on which machine or to which subnet.
In consequence, high-traffic networks can dramatically increase the system load in machines that are responsible to steer the traffic or block unwanted requests, up to the point where no routing is possible any longer (e.g., denial of service attacks).
This project aims at providing an efficient routing mechanism, directly implementable on FPGAs, i.e., on hardware, to free the operating system, and hence the main CPU, from this time consuming task as much as possible. The routing policy is to be specified in terms of some formalism (e.g., regular expressions, finite automata), which should then be mapped onto an FPGA for execution.
The main goals of this project are
- to analyse common routing policies and to examine which formalisms are suitable for capturing these,
- to devise algorithms for translating formal policies to FPGA programs,
- to find trade-offs between different types of translations resulting not only in differently large programs, but also in different means for their implementation,
- to implement and experiment with some of the found solutions.
The candidate to work on this exciting project is, ideally, familiar with a Unix-type operating system and the netfilter framework for specifying routing policies. This project will also require basic knowledge of formal languages and automata theory such as gained by having visited COMP3360/6363 (cf. also [2]).
References:
-
John E. Hopcroft, Rajeev Motwani, and Jeffrey D. Ullman.
Introduction to Automata Theory, Languages, and Computation.
Addison Wesley, 2000.
[TOC]
Algorithms for Efficient Manipulation of Boolean formulas
Supervisor: Dr. Jussi Rintanen, DPO Group (ANU) & Managing Complexity (NICTA)
After the success of Binary Decision Diagrams (BDD) in computer-aided verification and many other areas, there has been a lot of interest in identifying other normal forms of propositional formulas (Boolean functions) for which efficient (polynomial time) algorithms exist for the basic operations required in these applications. Research in the last 8 years have led to the identification of Decomposable Negation Normal Form DNNF which is more compact but allows a slightly more narrow set of efficient (polynomial-time) operations.
In the standard framework of Boolean function representations based on the connectives for Disjunction, Conjunction and Negation, the least restrictive form is that of general NNF (Negation Normal Form). This normal form always leads to at least as succinct representations as e.g. BDD or DNNF.
A practically interesting problem is the identification of more efficient but not necessarily polynomial-time algorithms for the manipulation of general NNF formulas. In comparison to BDD or DNNF, NNF are sometimes exponentially more succint. The seemingly efficient operations on BDD or DNNF could be simply a result of these normal forms being less succinct: a non-polynomial operation on NNF could conceivably be in absolute terms more efficient than a polynomial operation on the exponentially bigger BDD or NNF.
This project is an investigation of operations on NNF that are in absolute terms equally or more efficient than the operations on the equivalent BDD or DNNF. We know that such operations exist, because one way of implementing these operations is to first translate the functions to BDD or DNNF.
The goal of the work is the development of practically useful alternatives to BDD and DNNF representations that are based on the more succinct NNF.
Contact:
Dr. Jussi Rintanen
Research area: software engineering, formal languages,
algorithms Difficulty: medium Supervisor: Dr. Andreas Bauer (RSISE & NICTA) Related courses: COMP3360/6363 Background:
Regular expressions in Unix and many other systems allow the matching of
strings against user-defined expressions. In [1], trace patterns were
introduced, which are strings where some information is missing (i.e.,
strings which contain variables as place-holders), and it is shown that
the problem of how to match such incomplete strings against regular
expressions (given, e.g., in terms of a finite automaton) is decidable.
The GNU C-library [3] provides its own implementation of expression
matching, which is nowadays a standard in Linux and many Unix-like
systems.
The main goals of this project are to
The final implementations should also be tested and performance of the
implementation evaluated empirically.
This project will require familiarity with the C programming
language, and basic knowledge of formal languages and automata theory
such as having visited COMP3360/6363 (cf. also [2]).
References: Research area: software engineering, formal languages Difficulty: medium-high Supervisor: Dr. Andreas Bauer (RSISE & NICTA) Related courses: COMP3360/6363 Background:
Monitoring systems is useful during design time as a means of testing an
actual implementation before it ships out to the customers. However, it
can also be useful in the final product, at runtime, to make sure that
some system does not enter an invalid state leading to the failure of
the system when it runs.
In [1] an approach to monitoring based on temporal logic was devised and
a so called monitor generator implemented in terms of [2], which takes
as input a user-defined temporal logic specification, and outputs a
finite state machine, which processes a system's actions and decides
whether or not these satisfy or violate the specification (or neither).
The goal of this project is to
This project is likely to involve some form of low-level
programming, wrapping function calls, and other sorts of fun stuff, and
will therefore require deep familiarity with a programming language (I
am not picky about which one, really), and basic knowledge of formal
languages and automata theory such as having visited COMP3360/6363
(cf. also [3]). Ideally, there's also a background on temporal logic
and/or model checking.
References: This topic is proposed as part of the French-Australian Science and
Technology cooperation project "Planning Approaches to Sofware
Verification", whose partners are INRIA, ANU, and UWA.
Games are a computational model used in computer science, economics,
biology, and social sciences to name a few. The motivation for the
present project arises from the area of multi-agent planning in
artificial intelligence, but the results are applicable to other
areas.
Given a description of the possible states of the game, of the
states that are considered as winning positions, and of the actions
that agents can take in each state, the basic problem is to find a
winning strategy for a given agent coalition (a set of agents). Such
a strategy specifies the actions that the coalition agents must take
in each state, and guarantees that the coalition will end up in a
winning state, regardless of the actions taken by agents outside the
coalition. In the project, we focus on a slightly different problem,
where the coalition is not given. Instead, we want to find the
smallest size coalition which has a winning strategy. This is a
computationally hard problem, so we will be building efficient
algorithms which attempt to perform well on average. Such algorithms
will use symbolic representations of set of states based on binary
decision diagrams, and will automatically derive heuristics to guide
the search from the description of the input game.
The student will start from a basic algorithm idea, which (s)he will
flesh out, implement and extend to more complex cases such as: 1)
computing a coalition of minimal cost, given a specification of the
cost of collaboration, 2) partially observable games (agent decisions
are based on partial information about the current state of the game),
3) more complex objectives than just reaching a winning state.
This topic is proposed as part of a collaboration with
CNRS in the
framework of
the ROSACE
project funded by the French
Scientific and Technological Research Network for Aeronautics and
Space. ROSACE studies the design, specification, implementation
and deployment of a fleet of mobile autonomous cooperating robots with
well-established properties particularly in terms of safety,
self-healability, ability to achieve a set of missions and
self-adaptation in a dynamic environment.
In the ROSACE project, a high-level mission is expanded into a set
of goals which are allocated to the robots. The robots must act
cooperatively to achieve these goals, and this might require
explicitly delegating subgoals to other robots. Cooperatively
synthesizing plans of actions is still a largely open problem. The
student will design and implement a cooperative and distributed
version of a standard planning algorithm. The algorithm will have to
guarantee a number of desirable properties (termination, correctness,
etc). This will require becoming familiar with automated planning,
constraint satisfaction and distributed search methods.
This project is best suited to a student with interest and
background in artificial intelligence, distributed algorithms, and
with good programming skills.
Background:
Controlled magnetic confinement fusion offers the
possibility of an inexhaustible supply of energy with zero greenhouse
gas emissions. At the very high temperatures required to sustain a
fusion reaction (millions of degrees), the fuel mixture is in a
plasma state.
Magnetohydrodynamics (MHD) is the study of
magneticised plasmas, with applications ranging from solar flares
through to laboratory confinement. The study of such plasmas using
MHD in complicated toroidal magnetic confinement geometry
necessitates the use of numerically intensive PDE and eigenvalue
solvers. Different stability codes often include different physical
effects, and utilise a wide range of input parameterisations, and/or
coordinate systems. The benchmarking of results from different codes
is important in validating code predictions, especially in the design
of concept experiments. Such physics studies frequently involve
determining the equilibrium and stability across parameter sets and
configuration profiles. A
Figure
1: Cut-away of a concept Spherical Tokamak Fusion Power Plant (3GW
thermal, 1GW electric) Requirements: Students will need to have an
interest or be familiar in working in a range of numerical simulation
languages, Fortran 90, C; graphics visualisation languages such as
Matlab, and an interest in physics and sustainable energy. The
project suits a student at the interface of computational science,
engineering, and physics.
Student's gain: Experience in the science
of large scale numerical analysis, code parallelisation, and
addressing the coupling issues associated with different
configuration metrics. The skill base is portable to large scale
numerical analysis in any field. Wider outcomes include an exposure
to sustainable energy research.
The ANU Department of Computer
Science has been collecting student course enrolments, marks and
grades through its FAculty Information System (FAIS) for
several years.
The aim of this honours project is to develop data mining techniques
that allow analysis of the FAIS database with the objective to better
understand student performance, progress and retention. The questions
that the department is interested in include, for example: why
students stop studying computer science?, what correlations there are
between their marks in different courses?, can we predict that a
student will have problems in a certain course based on her or his
past performance?, can we identify students that might be at risk of
failing or dropping out of computer sciences courses early in their
studies?
This project will include the following components:
Supervisor: Peter
Christen
Background
Many organisations today collect massive amounts of data in their
daily businesses. Examples include credit card and insurance
companies, the health sector (e.g. Medicare), taxation, statistics,
police/intelligence and telecommunications. Data mining techniques are
used to analyse such large data sets, in order to find patterns and
rules, or to detect outliers.
In many data mining projects, information from multiple data sources
needs to be integrated, combined or linked in order to allow more
detailed analysis. The aim of such data linkages is to merge
all records relating to the same entity, such as a customer or
patient. Most of the time the linkage process is challenged by the
lack of a common unique identifier, and thus becomes non-trivial.
Probabilistic data linkage techniques have to be applied using
personal identifiers like names, addresses, dates of birth, etc.
The ANU Data
Mining Group is currently working in collaboration with the
NSW Department of Health, Centre for Epidemiology and
Research on the development of
improved
techniques and algorithms for large scale high-performance data
linkage. We have been developing an open source data linkage
system called
Febrl
(Freely extensible biomedical record linkage), which includes
modules for data cleaning and standardisation (of names, addresses,
dates of birth, etc.), deduplication, data linkage (or matching), and
geocoding.
For more information please have a look at our
publications as well as
presentations that describe our research in more details.
The following student projects address important issues within our
data linkage project.
Supervisor for all projects:
Peter Christen
One of the difficulties in data linkage research is getting access to
real world data sets containing real names and addresses, as such data
is protected by privacy and confidentiality regulations. Developing,
and testing new and improved data linkage algorithms therefore becomes
very difficult.
We have developed a data set generator (which is part of
Febrl). However, this generator is very simple, and various
ways of improving it are possible. For more details please have a look
at the recent publication
Probabilistic Data Generation for Deduplication and Data Linkage.
Student research project
The aim of this honours research project is to further explore how
our simple data set generator can be improved. This would include
analysing the literature in this area (artificially creating data
sets), analysing the existing data generator code, and developing
improved techniques that reflect reality more accurately. Issues
involved are:
A student working on this project would be involved through
One of the problems when linking large collections of data with tens
or even hundreds of millions of records is the complexity of data
linkage techniques. Potentially each record in one data set has to be
compared with every record in the second data set, resulting in a
quadratic complexity O(n2). Techniques known as
blocking are normally used to reduce the number of record
pair comparisons (for example, only records that have the same
postcode value are compared with each other). However, linking
large data sets still takes a lot of time.
Only a very limited amount of research has been done in this area (we
are only aware of four publications so far the deal with parallel data
linkage, including one of our own papers:
Febrl
- A Parallel Open Source Data Linkage System, PAKDD'04).
Student research project
The aim of this project is to develop parallel data linkage techniques
that allow the linking of large data sets on modern multi-core
computing platforms. Issues which have to be considered include:
A crucial step in the data linkage process is the classification of
pairs of records that are being compared into either matches or
non-matches. For example, consider the following two records
containing a name and address each:
Are these two records representing the same person, or two different
people?
In the past few years researchers from the data mining, machine
learning, and AI communities have explored various classification
techniques, including decision trees, genetic algorithms, clustering,
active learning, support vector machines, and instance-based
classifier to improve the classification of record pairs. Other
researchers have applied techniques from information retrieval and
database research to improve the linkage classification quality.
However, this research has been fragmented and so far no large study
comparing the many classifiers has been conducted using different data
sets (both synthetic and from the real world).
Student research project
The aim of this project is to (1) implement prototypes of different
classifiers and then conduct studies comparing their performance using
different data sets, and to (2) develop new - based on existing
methods - classifiers that are well suited for the data linkage
classification problem. Issues involved are:
The vision of the Semantic Web is to equip the World Wide Web with machine-processible and machine-understandable semantics,
so that the Web can becomes a universal medium of information and knowledge exchange for both computer and human being.
Towards this vision, a number of building blocks of the semantic web have been created, including the Resource Description
Framework (RDF), the Web Ontology Language (OWL) and several query languages such as SPARQL. It can be foreseen that in the
near future a lot of information on the Web will be described or annotated using these facilities, resulting in a large scaled
knowledge base. Creating a consumable interface for naive users to access such a large knowledge base is becoming a new challenge,
as traditional interfaces on databases or knowledge bases are programmer-oriented rather than user-oriented.
Goals for this project: In this project, we will design and implement a number of techniques to facilitate users' accesses to large scaled data sources on the semantic web.
Requirements: Students will need to be proficient systems programmers with good C++ or Java skills.
Student's gain: The student will work on an interesting research problem with potential impact on the future World Wide Web.
The work will be carried in a research group of CSIRO. The student will get an insight of the R&D in both industry and academia.
The results will include a working prototype that can be demonstrated in an international conference and a publication in an academic
journal.
Literature and Background: Database usability;
DBpedia -- a dataset for the semantic web.
Supervisor: Dr. Jemma Wu (jemma DOT wu AT csiro DOT au), Dr. Xuan Zhou (xuan DOT zhou AT csiro DOT au)
Extending GNU regular expressions matching with trace patterns
Matching linear and non-linear trace patterns with regular policies.
In M. Marin, editor,
Proceedings of the 22nd International Workshop on Unification (UNIF),
RISC-Linz Report Series, no. 08-11, pages 16-24.
Research Institute for Symbolic Computation, Johannes Kepler University,
Linz, July 2008.
[pdf]
(extended version to appear in proceedings of LATA'09)
Introduction to Automata Theory, Languages, and Computation.
Addison Wesley, 2000.
[TOC]
Systems monitoring via runtime verification
The good, the bad, and the ugly - but how ugly is ugly?
Technical Report TUM-I0803, Institut für Informatik,
Technische Universität München, February 2008.
[pdf]
[postscript]
Introduction to Automata Theory, Languages, and Computation.
Addison Wesley, 2000.
[TOC]
Title: Computing the Smallest Winning Coalition in a Multi-Agent Game
Description
References
Title: Distributed Planning
Description
References
Honors Projects
http://rsise.anu.edu.au/~marcus/
marcus.hutter@anu.edu.au.
General Reinforcement Learning Agents (GRLA)
Agent applications are ubiquitous in commerce and industry, and the
sophistication, complexity, and importance of these applications is
increasing rapidly; they include speech recognition systems, vision
systems, search engines, planetary explorers, auto-pilots, spam
filters, and robots [RN03].
Existing agent technology can be improved by developing systems that
can automatically acquire during deployment much of the knowledge
that would otherwise be required to be built in by agent designers.
This greatly reduces the effort required for agent construction, and
results in agents that are more adaptive and operate successfully in
a wide variety of environments [LH07].
Goals of this project.
Technically, the project is about a recent general approach
to learning that bridges the gap between theory and practice in
reinforcement learning (RL).
General-purpose, intelligent, learning agents cycle through
sequences of observations, actions, and rewards that are complex,
uncertain, unknown, and non-Markovian [RN03]. On the
other hand, RL is well-developed for small finite state Markov
decision processes (MDPs) [SB98].
Extracting the right state representations out of bare
observations, that is, reducing the general agent setup to the MDP
framework, is an art that involves significant effort by designers.
The project is to investigate (by simulations or theoretical) recent
models [Hut09] that automate the reduction process and thereby significantly
expand the scope of many existing RL algorithms and the agents that
employ them.
Requirements.
Student's gain.
Literature
Universal Artificial Intelligence (UAI)
The dream of creating artificial devices that reach or outperform
human intelligence is an old one. Most AI research is bottom-up,
extending existing ideas and algorithms beyond their limited domain
of applicability. The information-theoretic top-down approach pursued in
[Hut05] justifies, formalizes, investigates, and
approximates the core of intelligence: the ability to
succeed in a wide range of environments [LH07].
All other properties are emergent.
Goals of this project.
The fundamentals of UAI are already laid out,
but there are literally hundreds of open questions
(see the exercises in [Hut05]) in this
approach that have not yet been answered. The
complexity ranges from suitable-for-short-projects to
full PhD theses and beyond.
Requirements.
Student's gain.
Literature
Human Knowledge Compression Contest (HKCC)
Being able to compress well is closely related to intelligence as
explained below. While intelligence is a slippery concept, file
sizes are hard numbers. Wikipedia is an extensive snapshot of Human
Knowledge. If you can compress the first 100MB of Wikipedia better
than your predecessors, your (de)compressor likely has to be
smart(er). The intention of the Human Knowledge Compression Prize
[Hut06] is to encourage development of intelligent compressors/programs.
Goals of this project.
Some of the following four subgoals shall be addressed:
Requirements.
Student's gain.
Literature
On the Foundations of Inductive Reasoning (FIR)
Humans and many other intelligent systems (have to) learn from
experience, build models of the environment from the acquired
knowledge, and use these models for prediction. In philosophy this
is called inductive inference, in statistics it is called estimation
and prediction, and in computer science it is addressed by machine
learning. The problem of how we (should) do inductive inference
is of utmost importance in science and beyond.
There are many apparently open problems regarding induction, the
confirmation problem (Black raven paradox), the zero p(oste)rior
problem, reparametrization invariance, the old-evidence and updating
problems, to mention just a few.
Solomonoff's theory of universal induction based on Occam's and
Epicurus' principles, Bayesian probability theory, and Turing's
universal machine [Hut05], presents a theoretical
solution [Hut07].
Goals of this project.
Requirements.
Student's gain.
Literature.
Fast and Optimal Pathfinding on Game Maps
Description and Goals
Pathfinding involves computing a route between two given locations on a map,
while avoiding all obstacles.
The problem is important in many real-life applications, including games,
robotics, and GSP navigation.
Pathfinding problems are usually solved by running a search algorithm, such as A*.
A* is able to compute cost-optimal solutions but it can require significant memory and time resources.
Recent approaches use hierarachical abstraction to greatly speed up the process,
at the cost of losing the solution optimality guarantees.
In this project, we aim at designing a new algorithm that combines the speed of hierarchical methods
and the solution optimality guarantees of standard A*.
We do this starting from the observation that many path fragments are equivalent, and therefore there is no need to explore all of them.
Requirements
Student's gain
Supervisor
Adi Botea
adi.botea@nicta.com.au
http://abotea.rsise.anu.edu.au
Plasma MHD simulations of Concept
Fusion Power Plants
Project outcomes: Deployment of
MCT to multiple plasma MHD codes, algorithm development to undertake
configuration scans, and application to assess the stable operating
configuration of next generation fusion energy experiments.
Supervisor: Dr. Matthew
Hole Co-supervisor: Dr
Jay Larson
Email: matthew.hole@anu.edu.au email:
Jay.Larson@anu.edu.au
Data mining projects
Why do students fail? Data mining the DCS student database
(Computer Science honours project)
Note: Parts of this project will require a human ethics
clearance which is currently being applied for through the
Human Ethics
committee at the ANU Research
Office. Depending upon the outcomes of this application there
might be changes to this project.
Data linkage projects
Probabilistic data generation (Computer Science honours
project)
Parallelisation of data linkage techniques (Computer Science
honours project)
A student working on this project would be involved through
Improved record pair classification techniques (Computer Science
honours project)
Dr Smith, Peter
42 Miller Street 2602 O'Connor
Pete Smith
42 Miller St 2600 Canberra A.C.T.
A student working on this project would be involved through
Semantic Web projects
User Consumable Interface for the Semantic Web
Semantics in Sensor Networks
Background: Despite existing different domain-specific deployments and the heterogeneity of sensor networks and sensing data, sensor networks share a common feature: they all collect and periodically transmit information from some set of sensors, and they all must carefully manage limited power and radio bandwidth to ensure that essential information is collected and reported in a timely fashion. From a data storage point of view, one may think of a sensor network as a distributed database that is able to conduct query processing. This has led to the design and implementation of query processing a very popular topic. However, query processing in sensor networks works different from that in a traditional DBMS given that the former is resource constrained (e.g. limited energy, memory and computation ability). Furthermore, the volume of the sensing date can be very variable (e.g. different sampling rate) within a time period and the access to this data may be delayed arbitrarily due to the motion of sensors and the network latency. These add new challenges to the not yet fully solved query processing problem and more needs to be done to enable the success of sensor networks applications.
Project outcomes: In this project, we will investigate what the ³semantics´ can help to improve query processing - other than just conventional development of a schema for metadata about (semantic) transformation. Prototypes will be based on a real world problem. The Fleck platform (*Fleck* - the sensors and sensor operating system developed by
CSIRO ICT Centre) is available for prototyping work. The outcome will include a working prototype for the future work to be built on.
Requirements: Students will need to be familiar with C programming language.
Student's gain: Student will be working on one of the most interesting sensor networks issues with other research scientists from CSIRO. At the end of this project, students will gain insights into R&D from both industry and academia and are ready to explore other issues arising from sensor network applications.
Supervisor: Dr. Lily Li
Email: lily.li@csiro.au
Using semantics to better understand the Web
Background: The Semantic Web means different things to different people because it is very broad. It may mean:- RDF, Microformats, OWL
- web services
- AI techniques
- Simple and tangible applications
Project outcomes: A number of algorithms will be developed, and eventually leading to easy access to the information on the Web other than just key words search.
Requirements: Students will need to have knowledge/skills about (1) web services technologies; (2) good understanding of RDF, OWL and reasoning on OWL; and (3) C++/Java.
Student's gain: By keeping up with the latest developments in the Semantic Web, students will not only gain insights into the vision of the Semantic Web but also have some hand-on experience about how to realise the semantics on the Web. Algorithms developed in this project may have potential to be used by popular search engines to deal with unstructured information on the Web more efficiently.
Supervisor: Dr. Lily Li
Email: lily.li@csiro.au
Scalable Work Queues for Parallel Garbage Collection
Physical limits mean that future performance improvements in processor design will mostly come from increased application-level parallelism. Thus the ability for systems to scale well on parallel architectures is an extremely important issue. Since managed languages such as Java and C# have become dominant in the application development domain, the scalability of managed runtimes has become a critical research issue. In this project we explore the scalability of a fundamental data structure at the heart of a Java runtime system---a load balancing parallel work queue.
Supervisor: A. Prof Steve Blackburn, ANUGoals for this project
This project will examine the scalability and pathologies of the load balancing parallel work queue used by MMTk, which is the memory management toolkit used by Jikes RVM. Hopefully the project will either confirm the scalability of the existing system or identify (and implement) a more scalable work queue design.
Requirements
Students will need to be proficient programmers with a good basic understanding of computer architecture and parallel algorithms. The work will all be done in a slightly restrictive subset of Java, so experience with Java is essential. Experimental design and data analysis is key to the first phase of the project, so experience in this area will be an asset (of course there will be plenty of assistance from your supervisor, particularly in this area).Student's gain
The student will gain hands-on experience with an increasingly important problem in the context of the leading research infrastructure for managed runtime research, in the setting of a world leading team.
Literature
This is a well-focussed problem and does not require any significant background reading. The load balancing work queue is reasonably well insulated from the rest of the environment we work in, so a deep understanding of MMTk or Jikes RVM is not necessary. www.jikesrvm.org Contact Steve BlackburnArchitectural Analysis of Garbage Collection Behavior
Trends in microprocessor design are toward massively multicore chips. One direction within this burgeoning research area is that of asymmetric multicore design, where the cores within a chip are not homogeneous. In this setting some cores may serve very specific purposes. Given a) the centrality of garbage collection to managed runtimes, and b) the very limited requirements of garbage collection algorithms, it may make sense to have dedicated garbage collection cores. To this end, this project will explore the architectural "footprint" of a garbage collector with a view to ascertaining the base requirements for a dedicated garbage collecting core.
Supervisor: A. Prof Steve Blackburn, ANUGoals for this project
The project will use an architectural profiling tool (valgrind) to profile a range of garbage collection workloads and thus attempt to characterize the architectural requirments of garbage collectors.
Requirements
Students will need to be proficient programmers with a good basic understanding of computer architecture. The primary tool for this project will be valgrind, a publicly available virtualization tool written in C. The student working on this project should be an accomplished systems programmer.
Student's gain The student will work on a problem of great industrial and academic importance and will gain a solid insight into the behavior of managed runtimes, at the architectural level. This project is a logical starting place for a much deeper examination of the project and eventually, realization in an FPGA. LiteratureA basic understanding of garbage collection would be helpful, but is not essential. Henessy and Patterson's standard text on computer architecture ("Computer Architecture: A Quantitative Approach", 4th edition) is an invaluable starting point for this work.
Contact Steve Blackburn
Profiling Java Virtual Machine Performance
The performance of managed runtime systems and the applications which execute on them is a hot topic of academic and industrial research. However, dynamic compilation, feedback directed optimization, and concurrency each make performance analysis significantly more complex than in traditional ahead-of-time compiled, static environments such as C programs. This project will explore techniques for profiling the performance of virtual machines and applications running over them. These techniques will include sampling via interrupts (due to timers and/or hardware performance counter triggers) and direct instrumentation of compiled code. Additionally, the project will explore dynamic generation and maintenance of code annotations so that machine code and calling contexts can be tied back to source code in the application or VM source code.
Supervisor:A. Prof Steve Blackburn, ANU
Goals for this project
This project will implement a number of different profiling techniques and a basic mechanism for dynamic maintenance of mappings between machine code and source code, in the context of Jikes RVM, a widely used research JVM.
Requirements Students will need to be proficient systems programmers with a good C and Java skills.
Student's gain The student will work on a problem of great industrial and academic importance and will gain a solid insight into the behavior of managed runtimes. The work will be carried out in a world-leading research group and will be conducted within the leading academic research infrastructure for managed runtimes.
Literature and Background
Familiarity with a simple profiling tool such as gprof would be an asset.
Some interesting related work can be found at the following links:
http://portal.acm.org/citation.cfm?id=1134012
http://www.cs.utexas.edu/users/mikebond/pcc-tr-2007.pdf
Contact
Supervisor: A. Prof Steve Blackburn, ANU
Goals for this project
This project will start by trying to clearly identify the application-VM boundary in Jikes RVM, a widely used research JVM. The project will try to apply the OS metaphor of trapping from one context or mode to another. Depending on the student's ability and ambitions, the project could lead to much more ambitious goals such as enabling Jikes RVM to self host.
Requirements
Student's gain
The student will gain a deep insight into the design and implementation of managed runtime systems. The work will be carried out in a world-leading research group and will be conducted within the leading academic research infrastructure for managed runtimes.
Literature and Background
Supervisors:
Dr Peter Baumgartner,
Prof John Slaney
E-Mail:
Peter.Baumgartner AT nicta.com.au
Formal logic provides a mathematical foundation for many areas of
computer science. Logical languages are used as specification language
within, e.g., program development and verification, hardware design
and verification, relational databases, and many subfields of
Artificial Intelligence. Automated Deduction is concerned with the
design and implementation of algorithms based on logical deduction for
solving problems in these areas. Instance Based Methods
are a relatively new family of methods for Automated Deduction; they share
the principle of carrying out proof search by maintaining a set of
instances of input formulas and analyzing it for satisfiability until
completion.
I offer several research-oriented honours projects centered
around Instance
Based Methods, in particular in connection (experimentation/extension)
with our own Darwin system (http://goedel.cs.uiowa.edu/Darwin/).
Please see this
page for more details.
Supervisor:
A/Prof Sylvie Thiébaux,
Dr Anbulagan,
Dr Olivier Buffet,
Dr Jinbo Huang,
Dr Yannick Pencolé
Background
Composite systems feature simple components organised into a highly
reconfigurable and modular architecture, due to which they can
appropriately assemble to achieve complex operations. Examples include
web and grid services, energy distribution systems, water management
systems, chemical plant control systems, telecommunication and computer
networks, to name but a few.
In the "Supercom" project, we are interested in building Artificial
Intelligence tools to supervise such composite systems. These will need
to confer the system the ability to self-monitor (diagnose) and
self-organise (assemble, reconfigure) to achieve optimal performance.
In this framework, various projects are available on topics such as
decentralised diagnosis [1], decentralised planning [2] or diagnosis
using satisfiability and knowledge compilation methods [3]. The main
supervisor will depend on the project, but interactions with other
researcher should appear naturally. A strong background in computer
science, software engineering, or mathematics, and an interest in
artificial intelligence are required, as well as good programming
skills.
References:
Supervisors: Dr Michael Comton, Dr Mark Cameron (CSIRO) A/Prof Rajeev Gore, Dr Alwen Tiu (RSISE, ANU)
Background
This project is about writing a compiler for automatic synthesis of
'programs' from specifications. Given the specifications for services
S1,...,Sn and the specification of goal G the compiler will generate a
'program' satisfying G by using the services S1,...,Sn. This compiler
could be targeted to a number of possible settings. For example, the
specifications could describe web services and the goal in this case is
automatic generation of composite web services from other web services.
Alternitively, the specifications could describe components of a
security
system and the goal some larger securty property thus the compiler
automatically generates the larger security framework.
The Information Engineering Lab at CSIRO's ICT centre already has such a
compiler for web services [1], in which a logic mapping language relates
resources, such as data and web-services, to relevant concepts and
properties [2], and the composition compiler automatically translates a
high-level declarative composition goal into an executable workflow
responsible for orchestrating the data and web-service calls necessary
to
materialize the specified data product.
But, we are currently restricted to composing over services that have
stateless, functional and deterministic operations. We would like to
extend this composition environment to work with web-services that have
a
stateful interaction style (i.e. the operation/message that the service
can perform depends on the current state of the service and the service
state machine).
A published method for web Service composition [3,4,5] does so, by using
a modal logic and tableaux theorem proving. But it concentrates on
message flow, not data. We would like to integrate the two.
The project would involve investigating how to integrate both data and
state into the specification of services and a composition goal. The
outcome would be a logic for describing the specification of each and a
compiler that can automatically generate a 'program' satisfying the goal
by using the provided services.
The project would suit a student with an interest in logic and
specification.
Refrences
[1] Cameron, M. A., Taylor, K. L., Baxter, R. Web-Service
Composition
and Record Linking VLDB Workshop on Information Integration on the Web
(IIWeb-2004) Toronto, Canada, August 2004. URL:
http://cips.eas.asu.edu/iiwebfinalproceedings/31.pdf
[2] Cameron, M.A. and Taylor, K. (2005), First order patterns for
information integration, Proceedings of the 5th International Conference
on Web Engineering (ICWE2005), 25-29 July, Sydney, Australia. URL:
http://dx.doi.org/10.1007/11531371_25
[3] Daniela Berardi, Diego Calvanese, Giuseppe De Giacomo, Maurizio
Lenzerini, and Massimo Mecella (2004), Synthesis of Underspecified
Composite e-Services based on Automated Reasoning in Proc. of the 2nd
Int. Conf. on Service Oriented Computing (ICSOC 2004). URL:
http://www.inf.unibz.it/~calvanese/papers-html/ICSOC-2004.html
[4] Daniela Berardi, Diego Calvanese, Giuseppe De Giacomo,
Maurizio Lenzerini, and Massimo Mecella (2004), ESC : A Tool for
Automatic
Composition of e-Services based on Logics of Programs in Proc. of the
5th VLDB Workshop on Technologies for E-Services (TES 2004). URL:
http://www.inf.unibz.it/~calvanese/papers-html/TES-2004.html
[5] Daniela Berardi, Diego Calvanese, Giuseppe De Giacomo, Rick
Hull,
and Massimo Mecella (2005), Automatic Composition of Transition-based
Semantic Web Services with Messaging in Proc. of the 31st Int. Conf.
on Very Large Data Bases (VLDB 2005). URL:
http://www.inf.unibz.it/~calvanese/papers-html/VLDB-2005.html
Supervisors: Dr Mark Cameron (CSIRO) A/Prof Rajeev Gore (RSISE, ANU)
Background
The Information Engineering Lab has a logic-based service composition
framework that is being applied across a number of domains, including
Health Data Integration (Cameron et al)
http://cips.eas.asu.edu/iiwebfinalproceedings/31.pdf
and environmental management
http://www.iemss.org/iemss2002/proceedings/pdf/volume%20uno/304_cameron.
pdf .
A published method for web Service composition (Berardi et al 2004)
http://www.inf.unibz.it/~calvanese/papers-html/ICSOC-2004.html
http://www.inf.unibz.it/~calvanese/papers-html/TES-2004.html (Berardi et al 2005)
http://www.inf.unibz.it/~calvanese/papers-html/VLDB-2005.html
relies on a translation of finite-state machine representations of a
composition goal and stateful Web services into a modal/description
logic, PDL. Tableaux theorem proving can then be applied to find a web
service composition that statisfies the goal. This project would aim to
replicate and implement that basic approach, but considering alternative
logics to improve the scope of the compositions that may be achieved.
Supervisors: Chris Gunn (CSIRO) Henry Gardner (DCS ANU)
Background
This project will seek to characterise the effectiveness of eye-gaze tracking
as a human-computer interface for virtual environments. The concept is that
participants should be able to interact with projected images using a
combination of keyboard controls and eye gaze. By focussing their visual
attention on icons or images on the screen, users should be able
to select these icons or activate other interaction.
Two application areas of interest are the Mind Attention Interface for the
Wedge virtual reality theatre and a something-or-other system in which
participants stand in front of a half-spherical shell screen.
In the Mind Attention Interface, eye-gaze tracking equipment will be
integrated with electroencephalogram (EEG) equipment which measures
electric signals from the brain of a participant. Correlating eye-gaze
measurements of attention with EEG data would be a possible extension of this
project.
This project will investigate how to program the matrix-matrix multiply
kernel from the BLAS library, dgemm(), for the UltraSPARC T2,
optimizing it for both single core and multicore/thread performance. It
will also evaluate its performance. Since dgemm() forms the
computational heart of almost all dense linear algebra computations, it
is suprising that there seems to be very little work done on this topic
so far.
A variant/extension to this project is described below.
This project will investigate the efficiency of the highly
sophisticated OpenMPI
implementation of MPI on large-scale shared memory nodes, such as the
T2 (8 core by 8 strand SPARC) , Freemont
(an 8 x 2 CPU Opteron) and IBM OpenPower 720 (2 x 2 CPU x 2-way
multithreading) systems hosted in DCS.
It will begin by an investigation of the relevant algorithms used in
OpenMPI, concentrating on barriers and collective operations,
comparing them (where applicable) with corresponding
operations using threaded programming paradigms.
Supercomputers today are large-scale parallel processors, and the Top 500 list is
the most definitive ranking of the world's fastest. While the status of
this list is contentious, the list is based on the results of a single
benchmark - the Linpack benchmark - which in this case solves a (very)
large dense linear system. The list is dominated by Beowulf-style cluster computers: a
parallel computer using (typically Commercial-off-the-Shelf)
switch-based network to communicate between the processors.
There is a publically available open-source code for a highly optimized
benchmark called
High Performance Linpack (HPL). It is also highly tunable, but the
tuning currently must be done by hand. This is problematic, in the sense
that it requires both knowledge if the complex algorithms used in HPL
(beyond the understanding of most people who wish to use the benchmarks)
and of the (cluster) supercomputer itself. Furthermore, in the case of
clusters, this problem is exacerbated by the fact that the
cluster may be non-homogeneous (so the benchmark results may depend
on which parts of the cluster are selected), and by the fact that
by their nature clusters may be easily reconfigured. Thus, it is
highly desirable that this tuning process can be automated.
The LAPACK For Clusters (LFC)
project went partway in addressing this, in that some work on
determining, given p processors, to the best logical P x Q
logical processor configuration, where P*Q <= p was made.
However, automatically choosing the critical blocking parameter and a
plethora of algorithm variants remains to be done.
This project will investigate automatic tuning methods for the HPL
package for cluster computers. The search can be done statically, and
employ efficient empirical methods based on techniques such as the
Nelder-Mead simplex search, as is done for the ATLAS package (which
itself can be used as a component of HPL).
The project involves experimenting with a variety of simple and more
sophisticated tuning methods, and would evaluate their suitability in
this context. The DCS Saratoga cluster will form a suitable
experimental platform. The project has the potential for publishable
work and for the production of widely used open-source software.
Relevant references include the
IEEE Task Force on Cluster Computing ; a paper on
solving dense linear systems on this platform (exposing some
problems with HPL); Dongarra, J et al. Self Adapting Numerical
Software (SANS) Effort, IBM Journal of Research and Development
50(2-3), 2006; A Case Study of HPL Benchmarking and Tuning, Verdi March,
Technical
Report APSTC-TR-2008-01, 07 Jan 2008.
A Beowulf-style cluster computer is
a parallel computer using Commercial-off-the-Shelf switch-based network
to communicate between the processors. Clusters have proved a
highly cost-effective high performance computer model, and have largely
displaced the traditional massively parallel computers built with
expensive vendor-supplied networks.
A typical cluster tends to evolve, and hence tend to become
heterogeneous.
The efficient parallelization of applications using the Message Passing Interface
(MPI) is reasonably well understood for homogeneous clusters.
However, for heterogeneous clusters, which can not only have nodes
with different processor architectures but also sections of
nodes connected by different networks, the situation is still
far more challenging. In particular, differences in processor and
network speeds make it difficult to utilize the faster components
more effectively.
Using the Jabberwocky
heterogeneous cluster, this project will investigate techniques used so
far to parallelize (scientific/engineering) applications for
heterogeneous clusters. The project will then make a selection of these
applications and evaluate the effectiveness of these techniques on the
Jabberwocky. New or variant techniques may then be proposed and
evaluated.
Relevant references include the
IEEE Task Force on Cluster Computing home page, and
An Overview of Heterogeneous High Performance and Grid Computing,
by Jack Dongarra and Alexey Lastovetsky.
Simulation is playing an increasingly important role in the design and
evaluation of current and future high performance computer systems. Sparc-Sulima is an open-source UltraSPARC
SMP simulator, written in C++ and developed by the CC-NUMA Project. Sparc-Sulima
simulates an UltraSPARC processor by interpreting each instruction.
It has timing models which predict an UltraSPARC III Cu shared memory
processor performance to a high degree of accuracy.
Currently, Sparc-Sulima can simulate an unmodified Solaris (UltraSPARC)
binary (executable program). When that program executes a system call
trap instruction, the corresponding operating system effects are
`emulated' (the simulated computer state is updated directly, rather
than via simulating a lengthy and complex sequence of kernel-level
instructions), and simulated execution then resumes. This mechanism is
handled by the SolEmn emulation layer in Sparc-Sulima. Threaded
programs (e.g. using the pthreads Posix thread libraries)
ultimately access thread-related operating system services via the Solaris
_lwp (lightweight process) trap instructions. The limitation
of the current implementation is that, at any time, there can only be
one active thread per CPU. Such a limitation has been in all
emulation-based computer simulators in the literature also.
The aim of this project is to extend the emulation of the _lwp
trap instructions to remove this limitation. It will require
implementing thread switching, which can occur by time-outs, and also
by the _lwp_suspend and yield system calls.
The current thread context save/restore mechanisms will also
have to be extended. If successful, the work should be publishable
(along with the existing work on threads emulation).
An extension of this project, would be to investigate
which thread scheduling heuristics best approximate real machine behavior.
Relevant references include:
Kevin Skadron et al. Challenges in Computer Architecture
Evaluation, Computer, August 2003; and
papers from the
Sparc-Sulima home page.
Supervisor: A/Prof Weifa Liang
Background
Wireless sensor networks have received
significant recent attention due to their potential applications from
civil to military domains including military and civilian
surveillance, fine-grain monitoring of natural
habitats, measuring variations in local salinity levels in riparian
environment, etc. The sensors in sensor networks periodically
collect the sensed data as they monitor their vicinities for a
specific interest.
The sensed data can be transmitted directly to the base
station where the client
queries are posted, the base station then processes the collected data
centrally and responds to users queries. However, due to the fact
that each sensor is equipped with energy-limited battery,
the energy efficiency rather than the response time for each query
is paramount of importance in sensor networks.
The energy consumption for the above centralized processing is very
expensive. Instead, we adopt energy-efficient in-network processing,
i.e., the data gathering is implemented through a tree rooted at the
base station, and the data at each sensor has to be filtered or
combined locally before it is transmitted to its parent.
Unlike most existing assumptions that each sensor only transmits a fixed
length of message, we consider another data gathering, in which
the length of the message that each sensor transmits
to its parent is proportional to the sum of the message lengths
of its children and itself. Thus,
the total energy consumption at a node is proportional to the
length of the transmitted message and the distance
between the node and its parent in the tree. Specifically, on one hand,
we aim to find such an energy efficient spanning tree rooted at the
sink node that the network lifetime is maximized.
On the other hand, we prefer the approximate result
instead of the exact result in traditional data models for a given query,
since the communications among the sensors are fail-prone.
Under this circumstance, how close the approximate result is to the
exact result becomes the essential issue.
In summary, this project will be in pursue of energy efficiency on the
basis of database modeling in sensor network environments.
A student working on this project would be involved:
Supervisor: A/Prof Weifa Liang
Recent advances in microelectronic
technology have made it possible to construct compact and
inexpensive wireless sensors. Networks formed by such sensors,
termed as wireless sensor networks, have been receiving significant
attention due to their potential applications in environmental
monitoring, surveillance, military operations and other domains.
While these applications revealed tremendous potential for capturing
important environment phenomenon using sensor networks, they have
also posed certain associated limitations. One of the major
limitations of sensor nodes that they are powered by low power
batteries, which limit the network lifetime and impact on the
quality of the network. Energy conversation in sensor network
operations is thus of paramount importance. As most currently
deployed sensor networks are used for monitoring and surveillance
purposes, the sensed data generated by the sensor network must be
available for users at the base station, data gathering that
extracts and collects sensed data from sensors thus is one
fundamental operation in sensor networks. The energy conservation on
data gathering leads to prolongation of network lifetime. The study
of energy-efficient data gathering poses great challenges due to the
unique characteristics and physical constraints imposed on sensor
networks.
In this project we study the {it aggregate node placement problem for
data gathering}, which aims to place a few powerful aggregate nodes
to
a dense sensor network such that the network performance
can be significantly improved. Assume that a heterogeneous sensor
network consists of two types of sensor nodes: cheap sensor nodes
that have fixed identical transmission range and expensive aggregate
sensor nodes that have various transmission ranges. Aggregate nodes
have more energies, higher data transmission rate, and better
processing and storage capabilities than sensor nodes. The main task
of an aggregate node is to process and relay data for sensor nodes
and the other aggregate nodes. Due to expensive cost associated with
aggregate nodes, the number of them in a sensor network is very
limited, thus, they need to be placed in the network carefully in
order to increase the network connectivity, reduce the data
gathering delay, and prolong the network lifetime. Specifically, the
aggregate node placement problem for data gathering is as follows.
Given a sensor network consisting of $n$ dense sensor nodes that
are randomly deployed in a region of interest
and a few number of expensive aggregate nodes $K$ ($K<< n$), the
problem is to place the $K$ aggregate nodes in the region so that
the network lifetime can be further maximised by answering data
gathering queries.
Supervisor: A/Prof Weifa Liang
Background
Technological advances in recent years have enabled the
deployment of large-scalable wireless sensor networks (WSNs)
consisting of hundreds or thousands
of inexpensive sensors in an ad-hoc fashion for a
variety of environmental monitoring and surveillance purposes.
In these applications, a large volume of continuous sensed
data generated by sensors needs to be either collected
at the base station or aggregated within the network. Thus,
WSNs usually are treated as a virtual database.
The skyline query, as an important operator in modern databases
for multi-preference analysis and decision making,
has received much attention recently due to its wide applications.
In this project we consider the skyline query problem in WSNs. We aim to devise novel, distributed evaluation algorithms
for skyline query evaluation from the scratch. We also consider
the skyline maintenance within sliding window environments
by developing distributed maintenance algorithms for it.
We will conduct extensive experiments by simulation
to evaluate the performance of the proposed algorithms
in terms of multiple performance metrics including
the total energy consumption, the maximum energy consumption
among the network nodes, and the network lifetime.
A student working on this project would be involved:
Supervisor: Prof Tom Gedeon
Background
A number of projects are possible in this area. I am interested in a number of topics, such as extracting rules from neural networks, information retrieval using neural networks, data mining and feature selection, cascade neural network structures, hierarchical neural network structures, and neural network applications. I have published papers in all of these areas with former students so there is plenty of earlier work to build on. No previous experience with neural networks is necessary. Most projects will use the very popular backpropagation neural network training algorithm. If you are interested in neural networks and would like to see if you might want to do a project in this area, please e-mail me tom@cs.anu.edu.au or come and see me.
Example projects:
i. Cascade neural network stuctures can be built automatically without
making decisions as to the number of neurons required to solve a
problem by adding single neurons. This project would investigate the
use of larger chunks such as feature maps as cascade components,
which would be useful for recognising images (including faces).
ii. Rule extraction: Neural networks can learn complex tasks but face
the problem that human beings do not trust them as they can not
understand _why_ a particular decision is made. This project
focuses on rule extraction for explanation.
Supervisor: Prof Tom Gedeon
Background
A number of projects are possible in this area. I am interested in a number of topics, such as automated construction of fuzzy rule bases from data, hierarchical fuzzy systems, fuzzy interpolation, information retrieval using fuzzy logic,, universal approximators, and fuzzy logic applications. I have published papers in all of these areas with former students so there is plenty of earlier work to build on. No previous experience with fuzzy logic is necessary. If you are interested in fuzzy logic and would like to see if you might want to do a project in this area, please e-mail me tom@cs.anu.edu.au or come and see me.
Example projects:
i. Fuzzy document filtering: Web search engines return many documents
which are not relevant to queries. Fuzzy techniques to enhance the
results from search engines will be very useful. This project will
investigate a number of fuzzy techniques for this purpose.
ii. Combining uncertainty: Fuzzy logic is a technique which deals with
uncertainty well. Sometimes data contains multiple kinds or sources
of uncertainty. For example, a pedestrian could report that he saw
someone he was quite sure was stealing something. He was not certain
and his own reliability is another but different kind of uncertainty.
This project is to develop some methods to combine different kinds
of uncertainty in intelligence led investigation. (Data from a
company specialising in this area will be available.)
Supervisor: Prof Tom Gedeon
Background
There are several optimisation methods inspired by natural processes,
It has been shown that evolutionary algorithms are efficient tools for
solving non-linear, multi-objective and constrained optimizations.
The principle is a search for a population of solutions, where tuning
is done using mechanisms similar to biological recombination. The
operations the bacterial evolutionary algorithm were inspired by
microbial evolution. Bacteria can transfer genes to other bacteria, so
the rules are optimised in each bacterium.
Example projects:
ii. Making pictures: If bacteria encoded the components of an abstract
computer generated picture, an individual could identify nice and
not nice images repeatedly to generate some 'art' which is tuned
for their esthetic sense.
iii. Scheduling: A previous student has worked on a GA for University
exam scheduling. A comparison with bacterial algorithms would be
an interesting project.
Supervisor: Prof Tom Gedeon
Background
A number of projects are possible in this area. I am interested in a number of topics,
such as image processing for face recognition,
HCI research tool to collect facial images, biologically plausible architectures
for face recognition, building and modifying computer models of real faces.
No previous work on face recognition is necessary.
For the image processing topic, some experience with computer graphics
would be useful. If you are interested in face recognition
or some similar topic and would like to see if you might want to do a project in this area,
please e-mail me tom@cs.anu.edu.au or come and see me.
Example projects:
ii. Video annotation: Techniques such as PCA can recognise the same
face so long as the rotation/expression/illumination is not too
different. This can be used to recognise one person throughout
a segment of video.
iii. 3-D Face model: An average face 3D model can be constructed
from a single face image and animated via rotation, a simple
face expression model, or illumination. This can then be used
to recognise faces in multiple poses, expressions or lighting.
Supervisor: A/Prof Rajeev Gore
Background
The Australian Bureau of Statistics stores its census information as a
collection of tables with one row (record) for every individual with
many columns like age, sex, marital status, current occupation etc.
Such tables invariably contain errors, either introduced during data
collection, or during data entry. For example, the census data may
contain a record for a person named X who is aged 6, is married and in
high school.
Such data usually has an associated collection of extra conditions
which capture important inter-relationships between the columns of the
table. For example, the census table may have constraints like "the
legal age of marriage is 16" and "a high-school student is aged
between 11 and 18". According to these constraints, the entry for X is
incorrect since the entry breaks both conditions, so the obvious
question is to find a correction which is as close to the original as
possible.
The problem of finding an error in a data table is known as
error-localisation, and the problem of changing an incorrect record so
that it passes all the constraints is known as error-correction. The
standard method for solving both of these problems is called the
Fellegi-Holt method, but it is highly inefficient. Recently, Agnes
Boskovitz, a phd student with the RSISE, has shown a deep connection
between the Fellgi-Holt method and a well-known method from
propositional logic called resolution.
Efficient automated tools for performing resolution and associated
logical deductions are readily available. The project is to implement
the Fellegi-Holt method using these logical tools to gauge the
efficacy of this logical approach to data cleaning. If successful, the
prototype has huge potential in real world applications and will
almost certainly lead to a publication in an international conference
or journal.
Feel free to email me if you are at all interested in this project.
An interval is a continuum of real numbers bounded by its end-points.
Interval arithmetic performs operations on intervals rather than
using discrete floating point representations. As a consequence of
this errors associated with numerical rounding are automatically
propagated and accounted for. Moreover the mathematical properties of
intervals can be exploited to develop entirely new algorithms.
The concept of intervals is actually not new, but was considered by
Moore in 1965. What is relatively new is the fact that some hardware
vendors are now providing direct support for interval arithmetic
within their compilers/hardware.
In this project we wish to develop an interval code for evaluating
the type of integrals that are used in quantum calculations on atoms
and molecules. Evaluations of these integrals involves truncation of
an infinite series, followed by the application of a variety of
recursion relations. As a consequence the value of the final integrals
reflect both a series truncation error, and a rounding error which can
vary according to the recursive path taken. This project will study
the balance between these two sources of errors and the implication of
this in large scale quantum calculations.
This project will build on work undertaken in 2005 by honours student
Josh Milthorpe who studied the basic performance of interval
operations and use of intervals in fast multipole calculations.
You will also be part of a team working on interval related methods
funded from an Australian Research Council Discovery grant.
Every function, no matter how complicated, is executed on a computer
as a series of elementary operations such as additions,
multiplications, divisions and elementary functions like exp(). By
repeated application of the chain rule to those elementary operations
it is possible to obtain the derivative of any computed function in a
completely mechanical fashion. This technique is applicable to
computer programs of arbitrary length containing loops, branches and
procedures. In contrast to explicit evaluation and coding of a
derivative, automatic differentiation enable derivatives to be easily
updated when the original code is changed.
A number of programs
are now available to perform automatic
differentiation for code written in a variety of languages
The aim of
this project would be to use one of these tools to perform derivative
evaluations for some computational science applications. Specifically
in the modeling of systems at the atomic level derivatives with
respect to atomic positions are hugely important determining things
like the frequencies at which molecules vibrate. Myself and others
have spent large quantities of time and effort deriving expressions
for derivatives and then coding them. To automate this process and for
it to be relatively efficient would be very significant. Your
objective would be to explore this issue for some relatively simple
computational molecular science codes.
Background
Over the past 10 years graphics processing units (GPU) have become
ubiquitous in desktop computers. Modern GPUs now allow substantial
user programability that lets them be used for more general-pupose
computation. Indeed in a recent paper that was presented
at SC04, Fan et al detail their efforts to construct a
"GPU Cluster for High Performance Computing". In this work the authors
plugged in 32 GPUs to a Xeon cluster system and in so doing increased
the total theoretical peak performance of the machine by 512Gflops -
for a cost just under US$13,000!!
Tracking this development there has been a number of groups developing
programming environments that can exploit the GPU for general
computations. Details of many of these are available at the GPGPU web site. Two of particular
interest to this project are
Brook
and Sh. The former is
built on top of C while the latter is built on top of C++. Brook for
example extends standard ANSI C with the concept of a "stream", which
is a new data type representing data that can be operated on in parallel.
The aim of this project is to investigate the potential for using
the GPU in molecular science computations. The initial target
application is likely to be N-body simulations, as typified by the
simulation of atom motions. Careful consideration
will be given to accuracy, since currently the GPU is limited to
single precision computations. Thus the project will address two
issues, i) the in principle feasibility of using the GPU for these
types of problems, and ii) the scientific usefulness given the
current single precision limitation.
Supervisors: Richard Alexander,
A/Prof Alistair Rendell,
Peter Strazdins
InfiniBand networks provide for multiple, parallel system area
networks using the same physical hardware, using a concept called
Virtual Lanes. Virtual Lanes allow the network to be split for a
variety of purposes including the separation of HPC cluster
management, message passing and I/O traffic. There are a number of
parallel filesystems used in heterogeneous Linux clusters, with
the most widely used being PVFS2, GPFS, Lustre in addition to the
legacy NFS system. One possibility with large SMP nodes in a cluster
is to use InfiniBand virtual lanes and operating system virtual
machines in a way that allows nodes of a cluster to be used as both
compute nodes and filesystem storage nodes. This project will
implement the Lustre filesystem on a small test cluster with large SMP
nodes and the InfiniBand interconnect, using virtual machines in a
novel way to segregate compute functions from I/O.
References:
Supervisor: Dr Michael Norrish
This project would suit a student keen to work in an area involving
logic and proof, and the development of infrastructure to support
these activities.
When specifying systems formally, a significant error-finding benefit
can accrue simply from writing everything down in an expressive logic,
and getting it all to type-check. Working in this way allows users to
quickly deal with the “low-hanging fruit”; important bugs
that are easy to find.
The HOL system currently
doesn’t allow for this model of work very well. Part of the reason
for this is that script files for HOL inter-mingle SML (which is the
theorem-prover’s implementation language) and embedded bits of logic.
We would like to check the logic without having to be able to parse
(and execute) SML as well.
Therefore, the first aim of this project is to design a simple file
format in which users could write “SML-less HOL”, and to
then implement at least two tools for manipulating this format. The
first tool would be the type-checker. It would make sure that the
definitions and other logical material in the file actually made sense
at the level of types. The second tool would do all this and also
produce a genuine HOL theory, using the various definitional
facilities already present in HOL. This file format would need to
include mechanisms for referencing other files, where previous logical
developments had been built up.
The final stage of the project would be to implement a simple
declarative language for writing proofs. The issues here are similar
to those for definitions; to escape the use of files that include
(SML) code, and move to formats that are easy to parse and manipulate
as data.
Supervisors: Dr Michael Norrish
When using an interactive proof assistant, a powerful tactic for
finishing goals is the use of first order proof procedures.
Unfortunately, these procedures are all-or-nothing affairs: if they
succeed, they succeed completely, but if they fail to prove the goal,
the user knows only that the provided lemmas and assumptions were not
sufficient to allow the procedure to find a proof.
The advent of model generation tools promises a way out of this
painful situation. These tools can be used to generate what is
effectively a counter-example to false goals. This is much more
helpful for the user. Either the tool's output really is a
counter-example and their proof will never succeed, or the
counter-example will be impossible because the user has forgotten to
tell the tools some relevant lemma from a database of known facts.
The student's task in this project would be to implement a connection
between two existing tools: the interactive system HOL4, and the model
generation tool Darwin. This connection would provide a user-friendly
implementation of the scheme described above: when an invocation of
the first order prover in HOL failed, the connection implementation
would translate the HOL goal into terms that Darwin could understand,
call Darwin, and then finally translate Darwin's provided
counter-example back into a human-readable form for the user's
benefit.
This project would suit a student familiar with functional programming
(HOL is written in SML), and happy with the concepts of first order
logic (terms, formulas, quantifiers). The student would be jointly
supervised by Michael Norrish and Peter Baumgartner.
The Internet security has been
becoming more and more important as Cyber attacks have significantly increased
in volume, coordination and sophistication due to the spread of worms and
botnets. A botnet is a large collection of compromised machines under a common
Command-and-Control infrastructure, typically used for nefarious purposes. A
honeypot is a computer trap specifically designed to attract and detect
malicious attacks, in particular botnet attacks. For example, the Leurre.com
and the SGNet honeypots are distributed over 30 countries and they have
collected hundreds of gigabytes of Internet malicious traffics. This Honours project, as a part
of DSTO-NICTA joint honeypot project, is to improve or develop techniques for
discovering actionable knowledge from Internet malicious data collected by the
Leurre.com and the SGNet honeypots. The project may concentrate on following
topics, each of which could be developed into a quality Honours thesis. The new technique would be very
useful for proactive security, such as Internet intrusion prevention. Participants will have the
opportunity to get hands-on experience with some of the latest technologies.
The participants will access large real-world databases collected by honeypots.
They can experience both academic and industrial research work environments,
under supervision of Dr Warren Jin. Each student participant may receive
stipend for living expenses up to $1500 per semester depending on the
contribution to the honeypot project. Student participant should either have
excellent programming skills in Java, C++, or Python, or have strong
mathematical background. Experience of networking or Internet security or
database is useful. Knowledge of data mining, machine learning or statistics
is an advantage, but not necessary. Please
feel free to contact Dr Warren
Jin (Huidong.Jin@nicta.com.au)
for further information. Owing to the rapid progress on data
collection and advanced database system technologies and World Wide Web,
various complicated data have been explosively growing. There are lot of
examples of data streams. For
example, a satellite-mounted remote sensor is generating data constantly. World-wide
distributed honeypots are collecting malicious Internet traffic data every
second in order to monitor the spread of worms and botnets. These data streams
are massive (e.g., the Leurre.com and the SGNet honeypots are collecting
hundreds of megabytes data over 30 countries every day), temporally ordered,
rapidly evolving, various types of attributes (e.g., continuous, categorical,
string) and potentially infinite. Mining complicated data streams is one of
very important real-world data mining tasks. This Honours project is to
develop or improve a data mining technique on complicated data streams. The
data mining technique could be, but not limited to, data visualisation,
temporal association analysis, clustering, time series analysis, outlier detection
and classification. The technique can be used to find interesting events or hot
spots within data streams. The project will consider mixed data attributes such
as continuous (e.g., packet length), categorical (e.g., TCP or not) and
sequential (e.g., payload strings) attributes. The project may also take into
account of scalability for large amount of streaming data. Participants will have the
opportunity to get hands-on experience on up-to-dated stream mining techniques.
The participants may be engaged in using these techniques to handle real-world
challenges. They can experience both academic and industrial research work
environments, under supervision of Dr Warren Jin. Each student participant may
receive stipend for living expenses up to $1500 per semester depending on the
contribution to the use-inspired research. Interested students should have good
understanding of data mining, visualisation or time series analysis.
Programming skills in C++, MatLab or R are useful. Experience of databases or
data analysis or distributed computing is a plus. Please
feel free to contact Dr Warren
Jin (Huidong.Jin@nicta.com.au)
for further information. Population
projection is to compute, given certain assumptions about future trends, future
changes in population sizes for specific areas, say, states or cities.
Population projection is valuable. For example, population sizes are a
prerequisite for ensuring an adequate and appropriate supply of land for
sustainable city development, as the development is supported by the timely
delivery of commercial land, dwelling land, infrastructure and community
facilities. Collaborating with the ACT Planning and Land Authority (ACTPLA),
NICTA researchers have developed a stratified hidden Markov model to predict
population sizes for existing suburbs. It performs quite well in terms of data
independency, output flexibility and projection accuracy.? This Honours project
aims to extend these population projection techniques for new suburbs. Research challenges include small area, lack of
training data and scientific projection evaluation. Besides population sizes,
the techniques may take into account of other economic, social, environmental
and political factors. The participant will learn to solve real-world problems
using data mining techniques, such as temporal classification or clustering.
He/she will also learn to handle uncertainty for decision making. He/she will
experience how a novel technique is developed within an industrial research
organisation like NICTA.? Contact:
Warren Jin (Huidong.Jin@nicta.com.au)
or Yongxiang Xia (Yongxiang.Xia@nicta.com.au)
Bubble VM: the VM within the VM within the VM....
Surprisingly, and despite the stated advantages of managed languages (such as Java and C#), no commercial managed runtime systems are written in the language they implement. However, there are two successful research runtimes which take this approach, Jikes RVM (an open source Java-in-Java VM), and Bartok (an ahead-of-time C# system on which the Singularity OS project is built). Both of these projects have demonstrated considerable promise, and both have demonstrated that performance need not be a roadblock to such VM implementations. One of the most vexing issues faced by such VMs is the potential for blurring the distinction between the application and the host on which it runs. In this project we will explore how to better understand the boundary between the application and the supporting VM, using a rough analogy to the isolation that exists between user mode and kernel mode in a modern operating system. A good understanding to this problem could fundamentally change the design of such JVMs, increasing their reliability, improving their debugability, and improving security. Such a VM could run on any other VM and could run any application---thus could be self hosting and in principle could host an arbitrary nesting of instances of itself within itself!
Students will need to be proficient systems programmers with a good C and Java skills.
There is not a great deal of prior work in this area. However, the original paper describing Jalapeno (which became Jikes RVM) describes some of the most basic issues that a Java-in-Java design must face:
Projects offered by Dr Eric. McCreath
Instance Based Methods
Supercom
E-Mail:
sylvie.thiebaux-AT-anu.edu.au,
anbulagan-AT-nicta.edu.au,
olivier.buffet-AT-nicta.edu.au,
jinbo.huang-AT-nicta.edu.au,
yannick.pencole-AT-anu.edu.au
[1] Yannick Pencolé, Marie-Odile Cordier A formal framework for
the decentralised diagnosis of large scale discrete event systems and
its application to telecommunication networks, Artificial Intelligence,
Volume 164, Number 1-2, May 2005.
[W: http://www.informatik.uni-rier.de/%7Eley/db/journals/ai/ai164.html#PencoleC05]
[2] E. Amir and B. Engelhardt, Factored Planning, in 18th Intl' Joint
Conference on Artificial Intelligence (IJCAI'03), 2003.
[W: http://www.cs.uiuc.edu/~eyal/papers/factored-plans-ijcai03.pdf]
[3] Look-Ahead Versus Look-Back for Satisfiability Problems , Chu Min
Li and Anbulagan, CP, 1997, Linz, Austria.
[W: http://web.rsise.anu.edu.au/~anbu/papers/CP97Anbulagan.pdf]
A compiler for program synthesis
E-Mail: Mark.Cameron@csiro.au
E-Mail: Rajeev.Gore@anu.edu.au
Tableaux reasoning for web service composition
E-Mail: Mark.Cameron@csiro.au
E-Mail: Rajeev.Gore@anu.edu.au
Eye-gaze tracking as an interface for virtual environments
E-Mail:
Chris.Gunn@csiro.au
Henry.Gardner@anu.edu.au
Projects offered by Peter Strazdins
Basic Linear Algebra kernels for the T2 Multicore Processor
The Niagara or CoolThreads (T) series of processors has been motivated by
commercial applications such as web, database and eCommerce servers. Thus,
they have been able to achieve high throughput on workloads with many execution
threads, which are integer, memory and I/O intensive.
However, it has come equipped with a floating point unit on each core.
The question arises: how effective is it for (parallel) numerical
applications, and how can it be best programmed for these? Evaluation of the T2's Multithreading Performance
The T2 not only has 8 computational cores, but each core can
concurrently support 8 computational threads. The question arises: how
much speedup can you get from the multiple cores, and how much more can
you get out of the hardware threading? Furthermore, what is the best
way to synchronize software threads, running across different cores and
hardware threads? In what ways is such a processor different from a
traditional shared memory processor?
This project will build on the a previous project by Hugh
Blemings based on the OpenPower 720. It involves evaluating the T2
on memory- and compute- intensive parallel benchmarks and
synchronization algorithms.
Tuning the Message Passing Interface library for
large-scale Shared Memory / Multicore Processors
The Message Passing
Interface (MPI) is the standard programming paradigm for
distributed memory parallel computing, and many large and important
applications have already been written in terms of MPI, and have run
successfully on recent cluster computers. With the recent advent
of large-scale chip multi-processors, the issue emerges of how can
these applications can reap the potentially massive performance of the
new generation of clusters that will be comprised of a number of
processor chips connected by shared memory, where each chip is a chip
multi-processor. The simplest method for such applications to run a
separate MPI process on each CPU in the system, but the efficiency of
this depends on whether the MPI implementation is sufficiently
intelligent to make use of the fact that there will be large sub-groups
of processes that are running on the same node and hence can communicate
by much faster communication mechanisms.
Automatic Tuning of the High Performance Linpack Benchmark
(co-supervised by
Alistair Rendell and Warren Armstrong)
Parallelizing Applications on a Heterogeneous Cluster
Extended Threads Emulation in an SMP Computer Simulator
Energy-Efficient Data Gathering in Wireless Sensor Networks
E-Mail: wliang@cs.anu.edu.au
Energy-Efficient Aggregate Node Placement for Data
Gathering in Wireless Sensor Networks
E-Mail: wliang@cs.anu.edu.au
Energy-Efficient Skyline Computation and Maintenance in Sensor Networks
E-Mail: wliang@cs.anu.edu.au
Neural networks theory and applications
E-Mail: tom@cs.anu.edu.au
Fuzzy logic theory and applications
E-Mail: tom@cs.anu.edu.au
Bacterial evolutionary algorithms
E-Mail: tom@cs.anu.edu.au
i. Clustering using BEAs: Clustering is more usually performed by
gradient descent algorithms. BEAs should allow more interesting
clusters to be formed where there are complex evaluation criteria
for cluster validity. Objects clustered could be images (e.g. see
1.i or 4.ii), or text (e.g. see 2.i, 2.ii). Clusters could have
predefined target criteria, such as hierarchical structure of a
certain depth.
Face Recognition
E-Mail: tom@cs.anu.edu.au
i. View morphing: View morphing between two images of an object taken
from two different viewpoints produces the illusion of physically
moving a virtual camera. We generate compelling 2D transitions
between images. Initially we will use the same face with small
rotations and produce intermediate images to produce a realistic
QuickTimeVR head.
Data Cleaning Via Logic
E-Mail: rajeev.gore@anu.edu.au
Interval Arithmetic for Computational Science
Supervisor:
A/Prof Alistair Rendell
E-Mail: Alistair.Rendell@anu.edu.au
Automatic Differentiation
Supervisor:
A/Prof Alistair Rendell
E-Mail: Alistair.Rendell@anu.edu.au
Numerical Simulation on Graphics Processing Units (GPU)
Supervisor: A/Prof Alistair Rendell
E-Mail: Alistair.Rendell@anu.edu.au
MPI and Global File System I/O over InfiniBand using Virtual Lanes
E-Mail:
Richard@AlexanderTechnology.com,
Alistair.Rendell@anu.edu.au,
Peter.Strazdins@cs.anu.edu.au
Declarative theorem-proving
Email:
michael.norrish@nicta.com.au
Finding Models of Unsolvable First Order Goals
Email:
michael.norrish@nicta.com.au
Projects from NICTA researchers
Project I
Project Title: Knowledge
Discovery from Internet Malicious Data Collected by Honeypots
Supervisor: Dr Warren Jin
Keywords: Data Mining, Internet security, intrusion
Project II
Project Title: Large
Complicated Data Stream Mining
Supervisor: Dr Warren Jin
Keywords: Data stream mining, exploratory analysis
Project III
Project Title: Population
Projection for New
Supervisors: Dr Warren Jin and Dr Yongxiang
Xia
Keywords: Data mining, time series analysis, prediction
The project requires good modelling
or programming skills. Some familiarity with elementary statistics,
time series or data mining is useful. Supervision will be provided from
Dr. Warren Jin and Dr Yongxiang Xia. Successful applicant might receive stipend for living expenses up to $1000 depending
on the project progress.
