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Research projects in Information Technology

Displaying 1 - 10 of 17 projects.

Recordkeeping for Empowerment of Rural Communities in a Developing Country

The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information that is vital to their lives, such as information on their entitlements, public services, health, education or work opportunities. Timely access to information is essential to perform many economic, social and leisure activities. In today’s digital age, information is more and more often provided in digital form.

Supervisor: Dr Viviane Hessami

Environmentally friendly mining of cryptocurrencies using renewable energy

Blockchain technology and its popular cryptocurrencies such as bitcoin and Ethereum have most revolutionary technological advances in recent history, capable of transforming businesses, government, and social interactions. However, there is a darker side to this technology which is the immense energy consumption and potential climate impact of the blockchain and cryptocurrencies.

Connected Cars: Computational Models for Time-Critical Safety Applications

Connected vehicles need to be aware of their surrounding environments. This is impossible without being dependent on many sensory inputs. Sensor data is continually collected and analysed, in real-time in order to perform time-critical and delay-sensitive actions. There are two major challenges 1) limited computational resources (processing power and memory) on cars, 2) transfer of large sensory data to the cloud may is not feasible.

Closing the feedback loop

Student satisfaction with feedback is consistently low in higher education, and there is a lack of understanding regarding how students interpret and interact with feedback. Learning analytics promises to enhance feedback practice by providing real-time data and insights into learning behaviour and outcomes, so as to inform educational interventions. However, the feedback loop remains open without an understanding of how students make use of the received feedback or the #sustainability of such feedback practice.

Supervisor: Yi-Shan Tsai

Integrating novel technologies and modelling tools to predict species’ responses to global change

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.

Reinforcement Learning for Self-organised Task Allocation

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?

Supervisor: Prof Bernd Meyer

Save the Bees, one buzz at a time

In this project, we will use machine learning methods to diagnose the health status of bee colonies and individual bees.

Bee populations are threatened worldwide due to a number of factors, including parasites and virus infections, climate change, intensive farming, and other environmental stress factors. Australia, until recently, has been relatively protected from infections, but these are now increasingly taking place here as well. 

Supervisor: Prof Bernd Meyer

Machine Learning and Computer Vision for Ecological Inference

"A picture is worth a thousands words"... or so the saying goes. How much information can we extract from an image of an insect on a flower? What species is the insect? What species is the flower? Where was the photograph taken? And at what time of the year? What time of the day? What was the weather like on the day the photograph was taken? This project aims to extract useful ecological and/or horticultural data from digital images by analysing their content.