Batch correction of taxonomic data of the human gut microbiome for generalization of case-control classification

Next-Generation Sequencing (NGS) has made it possible to perform metagenomic sequencing of environmental microbiome samples. Colorectal cancer (CRC) benefits from early detection, and many studies find correlations between disease presence and abundance of species in samples of the microbiome. However, these studies are hard to reproduce and...

Multi-Level Fairness Framework: A Socio-Technical framework for Fairness Requirements Engineering in Machine Learning

Machine Learning models are begin increasingly used within the industry such as by financial institutions, governments and commercial companies. In the past few years, there have been several incidents where these ML models show discriminatory behavior towards particular groups of people, leading to unfair decisions that can have negative...

Classification Algorithm for Early Detection of Atrial Fibrillation: The Development of a Supervised Learning Method Using Photoplethysmography Signals for an ARM Processor

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia occurring in around 0.5% of the world population. AF is characterized by the rapid and irregular beating of the atrial chambers of the heart, which can cause lead to strokes and other heart-failures. To prevent these consequences the early detection of AF is paramount. Using...

What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing

Designing tasks clearly to facilitate accurate task completion is a challenging endeavor for requesters on crowdsourcing platforms. Prior research shows that inexperienced requesters fail to write clear and complete task descriptions which directly leads to low quality submissions from workers. By complementing existing works that have aimed...

Towards Achieving Gender Equality in Automated Loan Approval Processes

The consumer lending domain has increasingly leveraged Artificial Intelligence (AI) to make loan approval processes more efficient and to make use of larger amount of information to predict their applicants’ repayment ability. Over time, however, valid concerns have been raised about whether decisions made about individuals using these data...

Online Distributionally Robust Fault Classification: With an Application for Tritium's EV Chargers

This thesis presents a novel data-driven Fault Detection and Isolation algorithm for the public network of Electric Vehicle chargers of Tritium Ltd. Pty. The proposed solution is robust against marginal differences in data distribution as well as marginal changes over time due the state-of-the-art optimization techniques used. This is required...

Predicting voluntary employee turnover using core employee data

Voluntary employee turnover is the process of an employee voluntarily choosing to resign from a company. High voluntary turnover has been shown to have negative effect on both organisational and financial performance of companies. Therefore, if companies were to know which individuals would leave their company in the coming months, this would...