Ruairí O'Reilly

Ruairí O'Reilly

Lecturer in Computer Science at Munster Technological University. Research in Explainable AI, generative AI evaluation, biomedical AI, fairness and decision support.

Supervision

Selected research and dissertation supervision migrated from the previous site.

PhD research

  • Ryan Donovan — Modelling the Relationship Between Personality Traits and Basic Emotions: A Multi-Modal and Affective Computing Approach (PhD, 2025)
  • Urja Pawar — Explainable AI in Medical Domain (PhD, 2023)
  • Urja Pawar — Evaluating Hierarchical Medical Workflows using Feature Importance (PhD, 2021)
  • Muhammad Muneeb Saad — A Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysis (PhD, 2021)
  • Zachary Dair — A Complex Adaptive System for the Analysis of Psychobiological data and Personalised Healthcare (PhD, 2021)
  • Urja Pawar — Incorporating Explainable Artificial Intelligence (XAI) to aid the Understanding of Machine Learning in the Healthcare Domain (PhD, 2020)
  • Urja Pawar — Explainable AI in Healthcare (PhD, 2020)
  • Urja Pawar — Enabling Proactive Smart Healthcare via Artificial Intelligence (PhD, 2020)
  • Muhammad Muneeb Saad — Advancing GAN architectures for the Augmentation of Biomedical Image Datasets (PhD, 2020)
  • Urja Pawar — A Framework for Model-Agnostic Explainable Artificial Intelligence (PhD, 2019)
  • Ryan Donovan — Differentiation in Personality-Emotion Mappings (PhD)
  • Ryan Donovan — Improving Academic Performance Amongst First Years Computer Science Students Through Goal-Setting (PhD)
  • Ryan Donovan — A Workflow for Modeling Personality And Emotions to Enable User Profiling and Personalisation (PhD)
  • Ryan Donovan — Introducing PEM - A Workflow for Mapping Personality Traits to The Basic Emotions (PhD)
  • Ryan Donovan — Quantifying the Links between Personality Sub-Traits and the Basic Emotions (PhD)
  • Ryan Donovan — A Quantitative Model Mapping Personality Traits to Basic Emotions (PhD)
  • Ryan Donovan — Linear and Nonlinear Modelling in Personality Emotion Mappings (PhD)
  • Ryan Donovan — An Empirical Study Quantifying the Links between the Basic Emotions and Personality Sub-Traits (PhD)
  • Urja Pawar — (PhD)

M.Sc. dissertations

  • Nathan Ben David Pattison — Dynamic Video Targeted Temporal Inpainting via Gaussian Splatting (AI, 2025)
  • Yash Sandeep Modi — Co-evolutionary Level Generation and Agent Development: A Hybrid GAN-RL Architecture for Ensuring Playable Game Content (AI, 2025)
  • Shane Ward — SDCS-X: Enabling Open and Modular Software-Defined Control Systems in Discrete Manufacturing (SAD, 2025)
  • Amal Zackaria — Architectural Models for Master Data Management in Data Mesh (SAD, 2025)
  • Ahmed Ghanem — VolumeScaler Controller (SAD, 2025)
  • Felipe Tuyama de Faria Barbosa — Assessing Playability of Automated Piano Transcriptions with Heuristic Metrics Based on Music Theory (SAD, 2025)
  • Marwen Battikh — A Developer Friendly RBAC Enabled Micro Frontend Framework With Dynamic Discovery Support (SAD, 2024)
  • Mickael Mania — Addressing the Exploration-Exploitation Dilemma in Adaptive Software Systems (SAD, 2024)
  • James Mahoney — Enhancing Performance and Scalability in Containerised Environments through Thread Pool Starvation Detection (SAD, 2024)
  • David Garcia Lopez — Performance Analysis of Rust, C++, and C# in High-Load Transactional Systems (SAD, 2024)
  • Madalina Dragan — Evaluating Generatively Synthesized Diabetic Retinopathy Imagery - 22.12 (AI, 2023)
  • Wenchao Zhao — (AI, 2023)
  • Manfred Steyer — (SAD, 2023)
  • William Stack — (SAD, 2023)
  • Declan Williamson — WebTransport: An initial assessment (SAD, 2022)
  • Marcelo Flores — Improving User Interface Test Automation Efficiency (SAD, 2022)
  • Gyanendar Manohar — InceptionCaps: A Performant Glaucoma Classification Model for Data-scarce Environment (AI, 2022)
  • Cristian Feteseu — Clustering and Interpreting Heart Murmur data via Medical XAI (AI, 2022)
  • Shane Quinn — Real-time facial emotion recognition at the edge with model compression (AI, 2022)
  • Daniel Gallagher — Transfer Learning in Skin Lesion Classification (AI, 2022)
  • Brendan Lyden — A Deep Learning Approach to Sleep Apnea Detection (AI, 2021)
  • Madalina Dragan — Diabetic Retinopathy classification using a CNN trained on synthetic retina fundus images (AI, 2021)
  • Dave Walshe — Melanoma Classification based on Transfer Learning Methods (MSc SAD, 2021)

B.Sc. projects

  • Christopher O Grady — An Exploration into Algorithmic Traders and Risk in the Stock Market (Software Development, 2024)
  • WeiXuan Leong — Towards Open-Source: Refactoring and Migrating Legacy Systems as OS Solutions (Software Development, 2024)
  • Conor Pasley — Improving the Communication of Large Learning Models through Socio-Economic Personas (Software Development, 2024)
  • Matthew Byrne — Technology Enabled Care: Fall Prediction in Elder Care Facilities (Software Development, 2023)
  • Jakub Kucharski — Mental Health Well-being Companion APP (Software Development, 2023)
  • Jonathon Mahony — Tyre Mate - Tread depth estimation on a mobile device (Software Development, 2023)
  • Roshan Sreekanth — Comparing Machine Learning Algorithms used in Stock Market Forecasting (Software Development, 2022)
  • Vytautas Vosylius — Actionable insights from the visualisation and analysis of traffic data (Software Development, 2022)
  • Aaron Kelleher — Housing analysis (Software Development, 2022)
  • Adam Baldwin — Quantifying the Interaction between Mood, Academic Performance, and Goal-Setting (Software Development, 2022)
  • Zachary Dair — Classification of Emotive Expression Using Verbal and Non Verbal Components of Speech (PhD, 2021)
  • Joshua Desmond — Solving the university course timetabling problem using Constraint satisfaction methodology and Answer set programming (Software Development, 2021)
  • Fiach O’Neill — A Comparative Analysis of Probabilistic and Game Theoretic Methods in Imperfect Information Games (Software Development, 2021)
  • Iulian Gherman — Predicting the Price of Cars using Machine Learning Models (Web Development, 2021)
  • James Harty — Filtering user profiles on Stack Overflow, based on technical skill, to provide suitable candidates for recruiters (Web Development, 2021)
  • Zachary Dair — A bi-modal approach to emotion detection, using verbal and non-verbal components of speech (Software Development, 2021)