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The following thesis topics have been suggested by members of academic staff, they will give you some idea of the range and size of topics for the honours thesis.

The these topics show the interests of the staff and will help you find a supervisor in your area of interest.

You can simply choose one of these projects or define your own topic.

You should choose an area that interests you and then, with the help of your supervisor, find a problem to be solved or investigated in that area.

Suggested thesis topics

A Probabilistic Approach to Computing Composition Tables

Description: Composition-based reasoning is one of the most important methods used in qualitative spatial and temporal reasoning. For a relation model, usually the composition table was established manually. For large calculi, this is error-prone and not desirable. This project will experimentally study a probabilistic approach to computing the composition table of several directional calculi.

Goal for this project: To determine the composition table of several well-known point based qualitative directional calculi.

Requirement: Good math and programming skills

Student’s gain: The student will work on an interesting problem in qualitative spatial reasoning. S/he will work with active researchers in this area, will learn to solve challenging research problems. Results of this project may be published at well-known international conferences or journals. Potential PhD graduate positions in this group are possible.

Supervisor: , ARC Future Fellow
 

Achieving Confidentiality and Privacy in e-Health Records

The Electronic Health Records (EHR) is the central piece of e-Health. It is a digital format of personal health record which contains information about an individual’s current and historical health status as well as non-clinical administrative information. One of the major concerns is its security as the data is confidential to individual. It is a huge challenge to design security schemes that safeguard individual’s privacy. The aim of the project is to design and implement a secured multi-partition, role-based Electronic Health Record which has been partially investigated.

Requirements: Students will need to be proficient programmers with good C++ or Java skills.

Student’s gain: The student will have an opportunity to work on an interesting and real problem in e-Health. The results may be published in an international conference or journal.

Supervisor:
 

Agent Design using Simulation

Description: Simulation is becoming a powerful tool designing complex systems. Intelligent mobile robots are an emerging and exciting technology, but there is an urgent need to develop new approaches to robot design. This project will focus on the role of simulation in design using the design of a robot soccer team in a simulated world. Robot soccer is an exciting challenge that involves localization (where am I?), locomotion (how do I walk?) and strategy (what should I do?). Check out the (opens external site).

Goal for this project: To develop an understanding of innovative simulation methods in complex systems design using the Robot Soccer domain.

Requirement: Strong design and programming skills, a passion for innovative technologies, a desire and willingness to work in a cross-cultural team.

Student’s gain: You will learn new knowledge and skills in systems design using simulated worlds. In this project you will learn the architecture of robot soccer systems, 3D simulators and techniques of artificial intelligence. You will then apply this knowledge to help create a system that learns and automatically improves its own performance by playing and experimenting in simulations. There may be an opportunity to be a member of a new 3D Robot Soccer Team.

Supervisors: and - Innovation and Enterprise Research Lab)

Algorithms & software for probabilistic graphical models of genomes in mixed DNA sequence data

Project Description: The human body is comprised of 10 times more bacterial cells than human cells. Newly developed DNA sequencing and metagenomics technologies enable the microbial component of the human body to be directly quantified. These DNA sequencing instruments produce DNA sequence datasets ranging in size from Gigabytes to Terabytes, but owing to the nature of sequencing chemistry, the DNA sequence data is heavily fragmented, requiring assembly before it can be interpreted.

Genome assemblies can be represented as string graphs, e.g. directed graphs where the nodes are strings over an alphabet of four nucleotides, and graph edges represent adjacencies between strings of DNA that are observed in a biological sample. In a probabilistic setting, the edges can be weighted according to the observed frequency of the adjacency in the biological dataset. Analysis of long-range relationships in this graph is of great interest, having applications ranging from tracing the spread of antibiotic resistance to cancer genome analysis.

Goal for this project: This project focuses on developing a probabilistic graphical model representation of genome assembly so that it captures uncertainty in the sequence data.

Requirement: Proficiency in a programming language such as C++, Python, or Java. Familiarity with probability models, graph algorithms, and/or machine learning concepts. No knowledge of biology required.

Student's gain: This is an excellent opportunity for a motivated student to develop skills ranging from bioinformatics to statistical analysis of “big data,” with the potential to eventually develop into Ph.D. research or commercial applications.

Supervisor:   [Location: CB04.06.34] 

Behavior modeling system development

Description: The project aims to develop a system to incorporate behavior modeling building blocks developed in the team, and to support behavior representation and modeling. The system is expected to support behavior understanding and representation. This may involve the techniques we are developing for behavior informatics, a very critical and popular problem in both research and business.

Goal for this project: Candidate will work with researchers to implement the techniques developed into a system.

Requirement: Programming in Java or C

Student’s gain: Advanced knowledge and hands-on experience in advanced analytics and data mining, working with a big and experienced team. Candidate will collaborate with senior PhD students and research fellows. Well motivated candidates are encouraged, who may have great opportunity to do a PhD in data mining.

Supervisor: ()

Collaborative Context Aware Computing

Description: With the emergence of mobility and the plethora of mobile devices used within the inside (office/home) and outside, there is a greater need for devices to be aware of the context within which they are being used and to enable greater collaborative interaction and unified experience between devices (both mobile and static). This project aims to explore how devices can increase their awareness of other devices and their environment through environmental sensing. Technologies like UWB, Wi-Fi, Bluetooth etc can be used to enable and detect short range advertisement, discovery and potentially pairing of devices. For example, a mobile phone and TV may collaborate to provide the user with a richer more unified experience, where by the mobile phone becomes an input device to the TV.

Requirement: C/C++, Python programing. Knowledge of communication protocols, understanding of TCP/IP wireless standards like UWB, WiFi.

Student's gain: $1K scholarship for 6 months.

Supervisors: (UTS supervisor) , Dr. Justin Lipman Intel R&D Shanghai (external supervisor) () 

Compact representation of schematic operators in planning as satisfiability

Background : Many business or government processes now involve communities or teams that interact with each other to achieve a higher goal. These can be design teams working with user teams or groups formulating policies or strategies for social or business activities. Collaboration is important to keep people aware of what is happening in their business activity and provide advice on actions to take for the community as a whole to be productive.

Honours project : The project is to look at the possibility of using intelligent WIKIs (or other social software) to support communities and community interaction. The WIKI would not only store documents but include other features such as expert locator or intelligence collection and include support for social interaction that improves collaboration within the community.

Supervisor:

Developing ways to make visualisations of genes more understandable

Description: Biologists are faced with lo∂ng lists of genes from their biomedical experiments but it's hard for them to work out how the genes are related and what they mean. We add information from the Gene Ontology and visualise them with various methods. However, there's still more work involved in making visualisations more understandable. This project extends previous student's work to cluster genes and 'concepts' in visualisations to let them make more sense to the biologists, especially in the childhood cancer domain.

Goal for this project: methods to make sense of visualisations, using decision trees and clustering, etc.

Requirement: Should have some experience in data mining, but this is not an absolute necessity. Interest in bioinformatics a plus, but not essential.

Student’s gain: experience in data mining and visualisation in R & Matlab on real datasets, working with biologists from a major Sydney children's hospital, perhaps experience coauthoring a paper that will help in getting future scholarships.

Supervisor: - Knowledge Infrastructure Lab (KIL))

Energy-Efficient Data Centric Storage and Retrieval for Wireless Sensor Networks

How to store and deliver data in Wireless Sensor Networks (WSN) is a key research issue. Recently, we proposed a new Energy efficient, Shared and Data-centric information Storage and Retrieval scheme that focuses on minimizing the energy consumption in WSNs. The aim of the project is to explore various features of the design and investigate fully important issues such as redundancy, creation of non-essential traffic internally and energy wastage.

Students will need to be proficient 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 of Wireless Sensor Network and Distributed Data Storage. The results may be published in an international conference or journal.

Supervisor:

Global Interface of e-Commerce Website

Description: This project will build knowledge of the target users by conducting case studies of e-commerce sites and find important web features for international users as well as e-business organisations. It includes identification of target users and business organisations, developing global base for a common interface for e-commerce.

Requirement: Bachelor in IT, Computing Sciences, IT+Business or equivalent

Supervisor:

Graphical models with pmtk3

Description: Graphical models are powerful probabilistic models which model the conditional dependencies (better: independencies) between random variables. In our research program, we use graphical models mainly to model various types of actions, activities and behaviours.
pmtk3 (opens external site) is a large library which permits flexible and efficient building of many graphical models.

Goal for this project: The student should first familiarise him/herself with the notion of graphical models and their main related problems. To this aim, we'll make available materials and support. As the next step, she/he should then a) familiarise him/herself with Matlab and pmkt3; b) choose a specific model (or more, if time allows); and c) implement it in pmkt3.

Requirement: Good programming skills and a natural understanding of calculus and statistics.

Student’s gain: Graphical models are a portmanteau solution for many application problem, not just video monitoring. The experience gained can be useful in many fields of analytics.

Supervisors: and - Advanced Video Surveillance program)

High-impact behavior pattern mining

Description: The project aims to develop new algorithms and systems to discover discriminative behavior patterns that indicate high business impact. This may involve advanced techniques of sequential pattern mining and behavior informatics to conduct deep behavior analysis and understanding, a very critical and popular problem in both research and business.

Goal for this project: New algorithm and knowledge innovated that can be applied to real-world business problems.

Requirement: Data mining fundamentals, statistics, programming in Java or C

Student’s gain: Advanced knowledge and hands-on experience in advanced analytics and data mining, working with a big and experienced team. Candidate will collaborate with senior PhD students and research fellows. Well motivated candidates are encouraged, who may have great opportunity to do a PhD in data mining.

Supervisor: ()

High Level Reasoning for Domestic Service Robotics

Domestic assistive robots are intended to work alongside humans as aids. One of the research challenges is how to combine reasoning to effectively achieve advanced human robot interaction. In 2010 CAS developed a platform for HRI research (known as the RobotAssist Platform) and a series of algorithms for human-robot interaction and showcased these at that year's RoboCup @ Home league. The Platform builds on the navigation, object recognition, grasping and path planning capabilities we have already developed. However, for close physical cooperation between humans and robots, such as shared handling and manipulation of objects, there is a need for more sophisticated high level reasoning. From the limited knowledge of the environment and the instructions conveyed to the robot (verbal or non-verbal) a more comprehensive set of actions need to be derived. For instance, retrieving a drink for a human user would require knowledge of the location/appearance of the drink in question and the location/appearance of the human requesting the item. This study aims to investigate the available automated planning techniques (such as STRIPS) on the high level reasoning tasks in a domestic service scenario.

Goals for this project: The goal is to design an automated high level planner .

Requirements: Students will need to be proficient systems programmers with good C++ / Java skills.

Student's gain: The student will work on an interesting research problem within the RobotAssist project. The work will be carried out at the UTS node of the ARC Centre for Excellence in Autonomous Systems. The student will get an insight of the R&D in the field of Robotics within the 2nd largest Robotics research group in the world. The results will include a working prototype that can be demonstrated within the Robocup @ Home competition and a publication in an academic conference.

Supervisor: and

Human Detection and Recognition in Image Sequences

Detection of humans in urban scenarios has been a hot topic of research in the last decade, increased security fears, city planning and monitoring have been spurring these developments. The push to have mobile cameras monitoring the environment over the past few years has lead to development of a number of learning-based systems for detecting and localizing objects (or people) in images. The proposed methods detect humans using a variety of feature extraction techniques and effectively combine training models to achieve significant performance. This study investigates a real time implementation of a system capable of detecting humans using mixtures of deformable part models (DPM).

Goals for this project: In this project, we will design, implement and evaluate a GPU based implementation of DPM for person detection.

Requirements: The student should have good knowledge and experience with C++ programming. on a Linux environment. Knowledge of computer vision techniques is desirable but not mandatory.

Student's gain: The student will work on an interesting research problem within the RobotAssist project. The work will be carried out at the UTS node of the ARC Centre for Excellence in Autonomous Systems. The student will get an insight of the R&D in the field of Robotics within the 2nd largest Robotics research group in the world. The results will include a working prototype that can be demonstrated within the Robocup @ Home competition and a publication in an academic conference.

Supervisor:

Image processing and machine learning for assistive visual interaction

Description: This project aims to explore non-speech, non-tactile ways to interact with users to understand their communication patters and needs, in particular monitoring eye gaze and head pose with external camera(s) to infer what the user is trying to communicate across. The project is aimed at people with physical and/or mild cognitive disabilities that prevent them from interacting in any other way. Some preliminary work has already been carried out.

Goal for this project: The project aims to analyse via image processing and estimation techniques where a user might be focusing their attention in their interactions with other people and in the context of the given environment, and learn their responses to facilitate future communicative patterns.

Requirement: This is a software oriented project where skills in image processing (PCA analysis, feature extraction, monocular-stereo matching, etc) are advantageous. A sound understanding of linux, GNU C++ tools and subversion will be needed. Understanding of image geometries and machine learning techniques is a plus but not essential.

Student’s gain: A good understanding of image processing and machine learning techniques will be gained as a result of undertaking this project. There is a real possibility that part of this work may be carried out with an assistive healthcare institution. There is a strong social aspect to this projects, and therefore will be particularly rewarding for some students.

Scholarship/condition: CIMS scholarships/internships may be partly available

Supervisor:

Improving evolutionary computation with information theory

Description: Evolutionary computation (EC) is an AI approach that uses ideas from Darwinian evolution and natural selection to evolve computer programs (rather than write them)! Information theory is the underlying theory behind sending data through communication networks. Recently we've developed an approach to dramatically improve the performance of some EC techniques using information theory. This project will refine and extend that approach for genetic programming.

Goal for this project: develop methods and software prototypes using information theory in linear genetic programming and other areas.

Requirement: Should know what evolutionary computation is and a little experience in Java, C++ or Matlab.

Student’s gain: experience in EC, perhaps experience coauthoring a paper that will help in getting future scholarships.

Supervisor: - Knowledge Infrastructure Lab (KIL))

Improving visualisations of genes for childhood cancer by adding in information about metabolic pathways

Description: Biologists are faced with long lists of genes from their biomedical experiments but it's hard for them to work out how the genes are related and what they mean. We have developed visualisation techniques that use ontology information. The next step in improving these visualisations is to add information about metabolic pathways to see which genes affect one another. This project involves data mining from Internet databases and programming of our visualisation software.

Goal for this project: methods to add information about metabolic pathways into our visualisation software.

Requirement: Should have some experience in data mining, but this is not an absolute necessity. Interest in bioinformatics a plus, but not essential.

Student’s gain: experience in data mining and visualisation in R & Matlab on real datasets, working with biologists from a major Sydney children's hospital, perhaps experience coauthoring a paper that will help in getting future scholarships.

Supervisor: - Knowledge Infrastructure Lab (KIL))

Innovative and Sustainable Web Services

Description: This project will build models of innovative and sustainable web services through case studies of businesses based in different cultures. The model development includes study of success factors for supporting web services in a global context.

Goal for this project: build innovative web service models

Requirement: Bachelor in IT, Computing Sciences, IT+Business or equivalent

Supervisor:

Intelligent behaviours for semi-autonomous healthcare robotic assistive platforms

Description: The objctive of this project is to implement controls for seamless integration of higher-level capabilities in assistive robotics, such as the CIMS autonomous wheelchair and intelligent walker rollator platform.

Goal for this project: The kind of high-level behaviours include, for instance:

Different behaviours will require support from different sensorial feedback (cameras, lasers, depth rangers etc), all of which are available at CIMS. Some are already integrated in the platforms, while others require further work.

Requirement: This is a collaborative effort with two healthcare providers, resulting in a practical SW project with a marked social robotics aspect. It would suit motivated students with software development, keen to learn more about sensor fusion and integration. Knowledge of linux, GNU C++ development tools and software revisioning (subversion) is desirable. Experience with system architecture and integration will be advantageous but not essential. The robotics software environment ROS will be used, so understanding (or willingness to learn) ROS is advantageous but not essential.

Student’s gain: A good understanding of robotics software systems will be gained as a result of undertaking this project. Skills related to the wide field of HRI/HCI, and robotics planning/navigation will be gained as a result of undertaking this project.

Scholarship/condition: CIMS scholarships/internships may be partly available

Supervisor:

Intelligent Collaboration Technologies: Representing Social Knowledge and Dynamics

Description: In a world of global collaboration and telecommuting, effective collaboration and communication is becoming a major challenge for business. We are exploring ways that technology can be used to create informal and spontaneous collaboration. With your help, we will fit-out the research laboratory with RFID tags, cameras and touch screens; we will use smart-phones for location tracking and we will integrate all of these sensors into web-based collaboration tools. The objective of this project is then to understand social interaction and spontaneous innovation: we will build models of social interactions, to use artificial intelligence to predict behaviours and to provide helpful advice based on those models. Think Foursquare combined with Google Docs/Wave. Feel free to use your imagination, but as a starting point, consider a system that instantly reschedules your meetings for you when your phone notices that you’ve missed the bus.

Goal for this project: To discover novel means for supporting spontaneous innovation through intelligent collaborative technologies.

Requirement: Strong design and programming skills, a passion for innovative technologies, a desire to explore and play with new technologies.

Student’s gain: This project is a chance to explore social networks, artificial intelligence and mobile app development in a world class research lab. You will work in a team environment and help design the business of the future.

Supervisors: and - Innovation and Enterprise Research Lab)

Intelligent power-management and monitoring for homes and enterprises

Description: With the increasing costs of electricity and the world wide effort in reducing carbon emissions, new technologies and devices are required to enable individuals, businesses and countries to better manage their power usage. The aim of this project is to develop a power monitoring system for central monitoring and management of power usage insides homes and enterprises.

Requirement: C programing. PCB development experience. Good knowledge of electrical circuit design and related tools.

Student's gain: $1K scholarship for 6 months.

Supervisor: ()

Mobile and Augmented Reality Wireless Sensor Network Health Application Development

We have a team of academics and researchers developing prototypes for using wireless sensor networks for Body Area Networks for mobile health monitoring. Opportunities exist to interface these devices with mobile and mobile augmented reality (AR) interfaces through smart phones and tablet PCs to allow health data to be displayed on mobile devices and on the internet. Other sensor applications are also welcome.

Supervisors: - mHealth lab)

Personal Health and Fitness Monitoring Using Mobile Technologies

Description: Research and development of mobile applications whereby a person is monitored using various types of sensors (ECG, accelerometer, oximeter, GPS,…) and a smart phone (or a Tablet).

Requirement: Mobile programming skills, a desire to explore and play with innovative mobile technologies.

Student’s gain: The student will work on an interesting research problem with potential impact on the future of mobile health. The project can be used as a base for a PhD.

Supervisors: and - mHealth lab, Personal Health Monitor (opens external site))

Phylogenetic analysis for metagenomics and epidemiology

Project Description: Microbes in the wild live in populations that are subject to continuous evolutionary pressure. Next generation sequencing and metagenomics methods provide a candid view of how microbes, including pathogenic bacteria and viruses, survive in the wild. Using sequence data generated with instruments such as the Illumina MiSeq at the ithree institute, phylogenetic inference methods can be applied to trace the epidemiological history of pathogen outbreaks, and understand how the pressures of natural selection relate to the genes in the organisms.

Goal for this project: This bioinformatics-focused project involves applying phylogenetic methods to understand the strength of natural selection on bacteria and the relationship between genotype and phenotype. Inference of epidemiological links via similarity of phylogenetic diversity across metagenomic samples will be explored.

Requirements: Proficiency in a programming, scripting, or statistical analysis language such as Python, Perl, or R.

Student's gain: This will be an excellent opportunity for an advanced undergraduate to learn and further develop computational and bioinformatic skill sets.

Supervisor:   [Location: CB04.06.34]

Risk scoring model development

Description: The project aims to develop new models, metrics and systems to score risky transactions and customers for major banking areas, insurance area and public service area. This may involve advanced techniques of risk modeling and trust modeling, as well as data mining to conduct deep scenario analysis and understanding. The problem is motivated by a very critical and popular problem in major business sectors.

Goal for this project: New algorithm and knowledge innovated that can be applied to real-world business problems.

Requirement: Data mining fundamentals, statistics, programming in Java or C

Student’s gain: Advanced knowledge and hands-on experience in advanced analytics and data mining, working with a big and experienced team. Candidate will collaborate with senior PhD students and research fellows. Well motivated candidates are encouraged, who may have great opportunity to do a PhD in data mining.

Supervisor: ()

Self-interpretation in bondi

Goal for this project: Use the expressive power of bondi (higher-order functions, objects, pattern-matching) to build an interpreter for bondi in bondi, or a part of one. Sub-tasks include pretty-printing (already done), evaluation, parsing and type inference. This will help demonstrate the expressive power of the language, and underpin compiler development.

Requirement: Good understanding of programming principles and practice

Student’s gain: Further understanding of programming principles and practice. Contribution to development of an actual programming language.

Supervisor: - Language Design Laboratory)

Support for autonomous robotics rescue operations

Description: The robot iRobot Packbot Explorer () is a platform employed at CIMS to support research work into rescue operations (finding victims, mapping collapse building environments, path planning, etc). It is fitted with a range of sensors to enable the platform in undertaking these tasks (laser range finders, infra-red cameras, etc). The robot is currently controllable via the drivers developed for the Player robotics software, as well as other dedicated software tools developed for its wireless and on-board control. In this project, first of all this support will be extended to make full use of the more advanced open source meta-operating system for robots ‘ROS’ (see ). Then, reinforcement learning approaches will be studied to infer operator distraction for effective management of the autonomous operations of the robot.

Goal for this project: The project goals are two: implement functionality to drive the robot (consisting of a tracked base and an articulated arm) building up from current player drivers, to incorporate native ROS support. Then, employ temporal models (Markov Processes, CRFs) and Reinforcement Learning to infer operator “distraction” levels. The aim is to achieve better management of the platform during the rescue operation by estimating when the platform might be neglected and acting accordingly.

Requirement: This is a robotics software oriented project with a strong emphasis on Artificial Intelligent techniques. A sound understanding of linux, GNU C++ tools and subversion will be needed. Understanding of ROS is advantageous but not essential. Experience with Artificial Intelligence models (HMMs, MDPs, CRF, Q-learning, etc) will be advantageous, but not essential.

Student’s gain: A very good understanding of robotic software architectures and Machine Learning will be gained as a result of undertaking this project. Skills in distributed software and multi-tasking will be put into practice as they form a key part of ROS.

Scholarship/condition): CIMS scholarships/internships may be partly available

Supervisor:

Text mining in science

Description: Scientists have difficulty keeping up with the huge numbers of articles in journal papers that they must read to keep up in their fields. This project will develop methods and a software tool using text mining to scan journal databases to help scientists manage what to read.

Goal for this project: methods and a text mining tool.

Requirement: Should have some experience in data mining or text mining, but this is not an absolute necessity.

Student’s gain: experience in text mining, perhaps experience coauthoring a paper that will help in getting future scholarships.

Supervisor: - Knowledge Infrastructure Lab (KIL))

The National Broadband Network and Smart Home

The National Broadband Network is potentially Australian’s largest project that aims to provide the infrastructure essential for delivering a modern education system and an affordable healthcare system of the future. Potentially, it also enables other revenue-generating and useful services for all Australians. The aim of the project is to explore and investigate the ability of the NBN to supporting the quality of service of modern smart home. Students should have some basic knowledge of Computer Networks, programming and statistical analysis skills.

Student’s gain: The student will have a chance to design their own smart home with the help of this Fibre To The Premise (FTTP) infrastructure.

Supervisor: