This project is based on the paper "Academic Journals, Incentives, and the Quality of Peer Review: A Model", in which we analyse strategic interactions between scientists and science journals. Our results shed light on how different objectives for journals shape the strategies that scientists adopt when aiming to publish their work.
Honours and Minor Thesis projects
Displaying 71 - 80 of 213 honours projects.
Primary supervisor: Julian Garcia Gallego
The tennis tour is a series of tennis tournaments played globally over a calendar year, where professional tennis players compete for prize money and ranking points. The structure of the tennis tour is organised into different tiers for both men and women, including grand slam tournaments and ATP/WTA tour events. In this project we use stochastic processes to model and simulate the tour under different experimental rules.
Primary supervisor: Zhaolin Chen
Description:
Magnetic Resonance Imaging (MRI) stands as a cornerstone in medical imaging, providing non-invasive, high-resolution images of the human body's internal structures. Brain tumor segmentation from MRI scans is essential for precise diagnosis and treatment planning. MRI provides detailed views of brain structures and abnormalities, but challenges like image noise, contrast imperfections and tumor variations can make segmentation difficult.
Primary supervisor: Zhaolin Chen
Description:
The early detection of neurological abnormalities through Magnetic Resonance Imaging (MRI) is crucial in the medical field, potentially leading to timely interventions and better patient outcomes. However, the traditional diagnostic process is often time-consuming and subject to human error. This project seeks to improve this aspect by employing deep learning for anomaly detection in MRI scans, exclusively using images from healthy participants for model training [1].
Primary supervisor: Agnes Haryanto
Mental health is an ongoing issue in Australia. The cause of mental health can be due to a variety of reasons: workplace culture, high workloads, job insecurity, disparity in pay, lack of career advancement opportunities and turnover intentions. Mental healthcare workers are not able to cope with it and are suffering from burnout. There is a need to ease mental healthcare workers' workload and provide consistent patient triage with the help of technology. The project aim is to investigate the existing approaches and tools in facilitating mental health workers to perform efficient patient care…
Primary supervisor: John Grundy
This is one of our CSIRO Next Generation AI Graduates projects:
https://www.monash.edu/it/ssc/raise/projects
Note: *** Must be Domestic Student i.e. Australian or New Zealand Citizen or Australian Permanent Resident *** for RAISE programme
Project Description
We have an existing product that focus on mid-market service or product delivery companies. The product is offering a community solution that offers support around a specific product or service. We want to increase its capabilities to offer smart content moderation and smart responses.
Primary supervisor: Yasmeen George
Problem Statement: The forensic identification of human remains is a critical legal process, culminating in the issuance of a death certificate by the appropriate authority. It is a multifaceted procedure that integrates scientific evidence—from antemortem records to advanced DNA analysis, forensic odontology, and anthropology—to match unidentified remains with missing persons.
Primary supervisor: Carsten Rudolph
This project will explore different aspects of intellectual property violations in generative machine learning . There is sufficient research work in this project for at least two students. However, individual sub-topics are rather independent and don't necessarily require group work.
Topics can be summarised as follows:
- First item
- Second item
Primary supervisor: Wai Peng Wong
This project will apply feature selection techniques for identifying features that can effectively predict the Logistics Performance Index (LPI), building upon our previously published work [1].
Primary supervisor: Wai Peng Wong
This project aims to analyse the comments of Twitter on non-communicable diseases. Students are expected to carry out Aspects Detection to identify the specific aspects discussed in the tweets e.g., causes, transmission and symptoms. Subsequently, students are expected to conduct sentiment analysis utilizing tools like TextBlob or VADER, while also taking into account the importance of considering emojis to enhance classification accuracy.