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Research projects in Information Technology

Displaying 21 - 30 of 187 projects.


[Malaysia] AI meets Cybersecurity

AI is now trending, and impacting diverse application domains beyond IT, from education (chatGPT) to natural sciences (protein analysis) to social media.

This PhD research focuses on the fusing AI research and cybersecurity research, notably one current direction is on advancing the latest generative AI models for cybersecurity, or vice versa: using cybersecurity to attack AI. 

Machine learning based kinetic modeling on the thermal decomposition of plastic waste via pyrolysis

This project aims to develop a machine learning based kinetic model for an accurate prediction on the product yield and quality from the pyrolysis of plastic waste. The primary outcome of the Project is the development of a robust model that is effective in simulating the entire pyrolysis process at a relatively low computing cost, whereas its results will be sufficiently accurate to predict the composition and yields of the products.

Supervisor: Dr Jackie Rong

[Malaysia] - Integration of heterogeneous biomedical data for robust and interpretable prediction

Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work best for specific feature types. Interpretability is the ability of an ML model to identify the causal relationships among variables.

Supervisor: Dr Ong Huey Fang

Personal Future Health Prediction

This is one of our CSIRO Next Generation AI graduate programme PhD projects with Future Wellness Group:

https://www.monash.edu/it/ssc/raise/projects/personal-future-health-prediction

Note:  *** Must be Domestic Student i.e. Australian or New Zealand Citizen or Australian Permanent Resident *** for RAISE programme

Project Description

Supervisor: Prof John Grundy

Creating a turnkey solution to classify, predict and simulate behaviour from videos of rodents

Introduction

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.

Combating antimicrobial resistance through use of artificial intelligence and genomics

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.

Active Learning for Language and Multimodal Applications

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.

Event Extraction and Neuro-Symbolic Reasoning for Law Enforcement and Legal 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.

Supervisor: Dr Lizhen Qu

Privacy-Enhancing Technologies for the Social Good

Privacy-Enhancing Technologies (PETs) are a set of cryptographic tools that allow information processing in a privacy-respecting manner. As an example, imagine we have a user, say Alice, who wants to get a service from a service provider, say SerPro. To provide the service, SerPro requests Alice's private information such as a copy of her passport to validate her identity. In a traditional setting, Alice has no choice but to give away her highly sensitive information. 

Supervisor: Dr Muhammed Esgin