The research challenge for this project is to research, prototype and evaluate approaches to automatically capture multimodal traces of team members’ activity using sensors (such as indoor positioning trackers, physiological wristbands and microphones), using learning analytics techniques to make sense of sensor data from healthcare contexts. Depending on the trajectory that you take, examples of the questions that such a project could investigate include:
Honours and Minor Thesis projects
Displaying 131 - 140 of 216 honours projects.
Primary supervisor: Roberto Martinez-Maldonado
The aim for this project is to research, prototype and/or evaluate approaches to increase the explanatory effectiveness of the visualisations contained in analytics dashboards or similar support data-intensive tools. Explanatory visualisations are those whose main goal is the presentation and communication of insights. By contrast, exploratory visualisations are commonly targeted at experts in data analysis in search of insights from unfamiliar datasets.
Primary supervisor: Waqar Hussain
Disruptive technologies such as artificial Intelligence (AI) systems can have unintended negative social and business consequences if not implemented with care. Specifically, faulty or biased AI applications may harm individuals, risk compliance and governance breaches, and damage to the corporate brand.
Primary supervisor: Mladen Rakovic
In this project, we aim at surveying relevant computational tools/models used for automatic question generation, and then comparing the effectiveness of these tools/models by using existing datasets.
Primary supervisor: Michael Cowley
Amphetamine (AMPH) is a widely abused drug, but before it was restricted in use it was an effective
weight loss agent. We have shown that a distinct group of neurons controls a large part of the
body’s weight loss response to amphetamine. In 2017 a single cell RNA sequencing project was
published (Campbell, Macosko et al. 2017) that described transcriptional profiles of 21,000 neurons,
amongst which are the neurons we have shown mediate the weight loss caused by amphetamine.
Primary supervisor: Gavin Knott
The evolutionary back and forth between hosts and mobile genetic elements drives the innovation of remarkable molecular strategies to sense or conceal foreign genetic material. The Knott Lab uses bioinformatics, biochemistry, and structural biology to understand how CRISPR-Cas and other novel immune systems specifically sense DNA or RNA. We aim to better understand the function of nucleic acid sensors to harness their activity as tools for molecular diagnostics or as innovative biomedicines.
Primary supervisor: Roger Daly
Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive forms of cancer, with a high mortality rate. Therapies for PDAC are limited to chemotherapy, which has been ineffective to treat advanced stages of the cancer. Therefore, it is critical to identify biomarkers and develop targeted therapies, to improve early diagnosis and patient care. We have generated mass spectrometry (proteomics and phosphoproteomics) data from 15 PDAC patient-derived xenographs (PDX), which have been grown in mice.
Primary supervisor: Kim Jacobson
Immune protection provided by immune memory underpins successful vaccines and is mediated mainly by memory lymphocytes and long-lived antibody- secreting cells. In particular, B cell memory is key to providing a rapid and robust response upon secondary infection and continual serum antibody protection. We are working to elucidate the crucial epigenetic mechanisms that generate and maintain B cell memory, and how B cells may retain molecular and functional plasticity under chronic pathogenic pressure.
Primary supervisor: Jian Li
Antimicrobial resistance poses significant medical challenge worldwide. Misuse, overuse or suboptimal dosing of antibiotics are major driving factors of antimicrobial resistance. Pharmacokinetic/pharmacodynamic (PK/PD) modelling is critical for designing optimal antimicrobial therapies to maximise the efficacy and minimise the emergence of resistance. However, conventional PK/PD modelling is generally based on viable counting on agar plates after overnight culture and employs a population approach.
Primary supervisor: Jian Li
Antimicrobial resistance (AMR) has posed critical challenges to global health. The World Health Organization has identified carbapenem-resistant Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacterales as the top-priority pathogens urgently to be targeted for the development of novel therapeutic options. Recently, bacteriophage therapy has attracted extensive attention owing to its potential as novel antimicrobials to combat MDR pathogens.