Research projects in Information Technology

Advanced strongly typed languages like Haskell and emerging type systems like refinement types (as implemented in Liquid Haskell) offer strong guarantees about the correctness of programs.  However, when type errors occur it can be difficult for programmers to understand their cause.  Such errors are particularly confusing for people learning the language.  The situation is not helped by the cryptic error messages often produced by compilers.

We live and work in a world of complex relationships between data, systems, knowledge, people, documents, biology, software, society, politics, commerce and so on.  We can model these relationships as networks or graphs in the hope of reasoning about them - but the tools that we have for understanding such network structured data (whether algorithmic analytics or visualisation tools) remain crude.  Emerging display and interaction devices such as augmented and virtual reality headsets offer new ways to visualise and interact with data in the world around us rather than on screens.  This…

Testing self-driving cars is extremely difficult, as one has to account for a very large space of possible scenarios. In this project, we will explore the application of automated testing techniques, mainly in the area of search-based software testing to verify that the AI components of self-driving cars work as they should. This project is in collaboration with Professor Hai Vu and the Monash Connected Autonomous Vehicle (MCAV) team.

Defect prediction has been developed for more than four decades. Yet, a multitude of human aspects (i.e., both developers and end-users) have been rarely considered and incorporated. Thus, this project aims to focus on inventing theories and approaches for human-centric defect prediction to efficiently predict and explain non-functional requirement defects (e.g., accessibility issues and usability issues in Mobile Apps) that have the largest impact on end-users and humanity.

Adversarial Machine Learning (AML) is a technique to fool a machine learning model through malicious input. Due to its significance in many scenarios, including security, privacy, and health application, AML has attracted a large amount of attention in recent years. However, the underlying theoretical foundation for AML still remains unclear and how to design effective and efficient attack and defence algorithms are remain a challenge in the research community. Furthermore, most existing  AML algorithms can only apply to Euclidean space.

The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological variables such as network connection strengths between neural population networks underlying brain activity.

Motivation: In today’s increasingly digitalised world, software defects are enormously expensive. In 2018, the Consortium for IT Software Quality reported that software defects cost the global economy $2.84 trillion dollars and affected more than 4 billion people. The average annual cost of software defects on Australian businesses is A$29 billion per year.

When designing user interfaces, developers want to be able to position objects in a structured way such that controls are clear and neat.  In the past, absolute positioning and grids have been used for this purpose.  However, such rigid layout doesn’t now allow adaptive layout for interfaces that run on a variety of screen sizes or that need different control sizes due to application being internationalised into foreign languages.  For this reason, Apple introduced constraint-based GUI layout under the name Auto Layout for iOS developers.  With…

Digital versions of technical documents, like textbooks and academic papers, are usually produced as static PDF files. Research has shown that working with these on electronic devices is frustrating and inefficient, partly because people do not read such documents in a linear fashion as they do novels.

This PhD project will investigate how existing book contents (text and graphics/animations) can be automatically translated into accessible eBook formats with minimum human intervention. It will be part of the Books for the Vision Impaired and the GraVVITAS frameworks (www.monash.edu/it/inclusive-tech). The project will employ computer vision, image processing and human computer interaction techniques. It may also include hardware development of wearable assistive devices that use audio and haptic feedback.