Research projects in Information Technology

There are sometimes emerging prolonged periods of highly persistent evolution in time series.

Education, undoubtedly, is one of the most fundamental means for people to gain personal and professional development. Given its importance, both researchers and practitioners have endeavored to apply various technologies to construct numerous educational systems and tools to facilitate teaching and learning in the past decades. For instance, with the development of Web technology, a large number of online learning platforms and web-based learning management systems have been developed and deployed for use, e.g., Khan Academy, Coursera, edX, Moodle, and Blackboard.

Species’ distributions are shifting in response to global climate change and other human pressures. Accurate methods to monitor and predict distribution shifts are urgently needed to manage threatened species and ecosystems, and to control invasive species and diseases. This requires a step-change in the data and methods used to monitor and predict organism behaviours and ultimately shifts in species' distributions.

This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful applicant will work as part of a larger research team.

Effective allocation of tasks is essential for any socially living group. This project investigates self-organised task allocation, ie groups in which tasks are not centrally assigned to individuals. In self-organised groups, individuals rather select their tasks autonomously based on their own choices and preferences. Under which conditions does this achieve the desired group outcomes?

We have a range of potential research projects on offer in partnership with VIFM - https://www.vifm.org/ - looking at ML techniques in predicting forensic diagnoses  / image analysis, across multiple data types found at VIFM. These include atomic data, text data and text documents, medical images, clinical photographs and digital pathology slides. 

This research has high potential to support our IT for social good agenda in addition to its technical attractiveness. 

Reasoning, constraint solving and optimisation technologies have made remarkable progress over the last two decades. A number of formalisms like Boolean satisfiability (SAT), satisfiability modulo theories (SMT) and their optimisation extensions (MaxSAT and MaxSMT) as well as constraint programming and optimisation (CP) and mixed-integer linear programming (MILP) can be seen as success stories in computer science.

The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon our groundbreaking research into the problem.

The world is dynamic and in a constant state of flux, yet most machine learning models learn static models from a dataset that represents a single snapshot in time. My group's research is revolutionising the field of temporal analytics. We have refocused the field on methods that are both effective and feasible for non-trivial problems.

This project works with leading researchers in the Faculty of Pharmacy to develop new artificial intelligence technologies to aide discovery of drugs to treat pharmacoresistant epilepsy.