Displaying 1 - 10 of 96 projects.
Rodent behavioural testing is the study of the neural mechanisms underlying emotions [1]. It is used in the study of almost all mental conditions, including PTSD [2], OCD [3] and autism [4]. For example, to measure anxiety, researchers may place a rodent in a large tub, record a top-down video and measure the time spent near the safety of walls [2]. These videos also contain rich information about behavioural patterns, but scoring this manually is time consuming.
Antimicrobial resistance (AMR) is one of the most significant and immediate threats to health in Australia and globally. We are working on harnessing new technologies such as artificial intelligence and next-generation sequencing and to improve the diagnosis, treatment and prevention of AMR infections.
The specific aims of this project are:
1. Rapidly identify AMR and predict treatment responses through use of genomics and machine learning in a clinical context.
This PhD project aims to mitigate the data scarcity of new NLP and Multimodal applications by developing novel active learning algorithms. In this project, the student will leverage large foundation models, such as ChatGPT and GPT4, incorporating the cutting-edge techniques in the other areas, such as reinforcement learning, causality and GFlowNets, to devise novel active learning algorithms for NLP and multimodal applications.
In recent years, social media have become a common plattforms for criminals to stalk, intimidate, manipulate and abuse vulnerable citizens, such as women and youth. A recent survey of students in grades 6 to 9 found that the rates of electronic bullying for girls were between 16% and 19%, whereas the rates for boys were between 11% and 19%. 33.47% of sexually abused girls reported experiencing cyberbullying compared to 17.75% of nonsexually abused girls.
PhD Studentship Description:
Project description
Microgrids aggregate distributed energy resources, bringing energy security to customers, from individual residences to businesses. Microgrids can contribute to net-zero transition to mitigate climate change in the energy sector by integrating renewables, storage, and consumer energy resources, such as demand-responsive loads.
The ability to capture carbon is expected to play a key role in the fight against climate change. A new apparatus is being developed at Monash University to capture carbon dioxide (CO2) from the air. This important technology provides a pathway to decrease the CO2 concentration in the atmosphere. A model of the apparatus needs to be developed in order to validate and understand its daily operations.
One of the main roadblocks to widespread electric buses is the charging of their batteries. Charging an electric battery takes substantially longer than filling up a petrol tank: 30-60 minutes with a fast charger, up to hours with a slow one. The drawback of fast chargers is that they are more costly and that it only takes a few of them to generate a substantial load on the current grid. This means that, compared to petrol buses, some changes might need to be introduced in how electric buses are operated.
Synthetic data generation has drawn growing attention due to the lack of training data in many application domains. It is useful for privacy-concerned applications, e.g. digital health applications based on electronic medical records. It is also attractive for novel applications, e.g. multimodal applications in meta-verse, which have little data for training and evaluation. This project focuses on synthetic data generation for audio and the corresponding multimodal applications, such as mental health chatbots and digital assistants for negotiations.
Portable point of care medical devices have revolutionised the way in which people receive medical treatment. It can bring timely and adequate care to people in need but also opens up the opportunity to address the healthcare inequality for the rural and remote.