"Evaluation Criteria for Trustworthy Artificial Intelligence"

Louise McCormack and Malika Bendechache

"Exploring Chronic Disease Trends among Adults in the USA: A Statistical Analysis with Visual Insights"

Vuong Ngo, Geetika Sood, Fionnuala Donohue, Patricia Kearney, Jennifier Pallin and Mark Roantree

"Automatic Speech Recognition Models for Pathological Speech: Challenges and Insights"

Kesego Mokgosi, Cathy Ennis and Robert Ross

"Employee engagement with a digital wellbeing platform: insights from association rule mining analysis"

Gillian Cameron, Maurice Mulvenna, Raymond Bond, Edel Ennis, Siobhan O'Neill, David Cameron and Alex Bunting

Keynote speaker: Susan Leavy

Title: AI, Society and Collective Intelligence

Abstract: AI is having a transformative impact in the world. It is being used in ways that can have a profound impact on society and could dramatically alter the information ecosystem. This talk will discuss the effects AI is having in society. The focus will be on how large language models could alter our information ecosystem and how people acquire knowledge. Societal effects, both seen and predicted, will be discussed along with new and emerging initiatives to mitigate risk.

"Mitigating Bias in Medical Datasets: A Comparative Analysis of Generative Adversarial Networks (GANs)"

Mohamed Ashik Shahul Hameed, Asifa Qureshi and Abhishek Kaushik

"Back-filling Missing Data When Predicting Domestic Electricity Consumption From Smart Meter Data"

Xianjuan Chen, Shuxiang Cai and Alan Smeaton

"The Impact of Feature Quantity on Recommendation Algorithm Performance"

Lukas Wegmeth

"Neural Architecture Search for Crop Yield Prediction using Multimodal Data"

Heera Lal Khatri, Paul Greaney, Jade Lyons and Thomas Dowling

Image Retrieval with Short Text Queries

Ojas Rane, Brian Mac Namee and Conor Nugent

"Generative AI-Enabled Chatbot for Improving Students Understanding and Awareness of Academic Integrity Policies"

Claudio Gonzalez and Faithful Onwuegbuche

"k-Most-Influential Neighbours: Noise-Resistant kNN"

Matt Mallen and Derek Bridge

"AI-Informed Development for a Lactate Measurement Tool"

Cian Kiely, Nicola Rossberg, Shree Krishnamoorth and Andrea Visentin

"Street Navigation for Visual Impairment using CNN and Transformer Models"

Hasan Ali and Faithful Onwuegbuche

"Deep Learning Pipeline for Blood Cell Segmentation, Classification and Counting"

Abhijeet Rao, Kiang Wei Kho, Vitaliy Mykytiv and Andrea Visentin

"Datasheets for Healthcare AI: A Framework for Transparency and Bias Mitigation"

Marjia Siddik and Harshvardhan Pandit

"Machine Learning Physical Fatigue Estimation Approach Based on IMU and EMG Wearable Sensors"

Suraj Prasannan Nair, Marco Sica, Salvatore Tedesco and Andrea Visentin

"Why are Some Vision Models More Robust Than Others?"

Róisín Luo, James McDermott and Colm O'Riordan

"Exploring the Potential of Bilevel Optimization for Calibrating Neural Networks"

Gabriele Sanguin, Arjun Pakrashi, Marco Viola and Francesco Rinaldi

"Data poisoning attacks in the training phase of machine learning models: a review"

Mugdha Srivastava, Abhishek Kaushik, Róisín Loughran and Kevin Mc Daid

"Extending TWIG: Zero-Shot Predictive Hyperparameter Selection for KGEs based on Graph Structure"

Jeffrey Sardina, John Kelleher and Declan O'Sullivan

"An investigation into the application of Anomaly Detection and the Meijering filter in the eKYC process to detect recaptured identity documents"

John Magee, Stephen Sheridan and Christina Thorpe

"Handling class imbalance via counterfactual generation in medical datasets"

Asifa Qureshi, Abhishek Kaushik, Gilbert Regan, Kevin Mc Daid and Fergal Mc Caffery

"Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification"

Davide Italo Serramazza, Georgiana Ifrim and Thach Le Nguyen

"Tangentially Aligned Integrated Gradients for User-Friendly Explanations"

Lachlan Simpson, Federico Costanza, Kyle Millar, Adriel Cheng, Cheng-Chew Lim and Hong Gunn Chew

"Towards Understanding Deep Representations in CNN: from Concepts to Relations Extraction via Knowledge Graphs"

Eric Ferreira dos Santos and Alessandra Mileo

"A global post hoc XAI method for interpreting LSTM usingdeterministic finite state automata"

Gargi Gupta, Luca Longo and M. Atif Qureshi

"An Explainable Genetic Programming Approach to Safely Predict Cyberbullying Occurrence in Ireland."

Aidan Murphy, Mahsa Mahdinejad, Saeed Ahmad Syed, Joe Kenny and Anthony Ventresque

"On the Benefits of Directness in Virtual Characters for Motivational Interviews"

Michael O'Mahony, Cathy Ennis and Robert Ross

"Investigating the impact of internal inputs on ‎multisensory integration: a ‎study of external ‎multisensory inputs and internal arousal"

Zahra Azizi, Jason Chan, Tomas Ward and Annalisa Setti

"Multi-Objective Mixed Bus Fleet Charging Schedule Problem with Time-of-Use for real-world data-sets"

Padraigh Jarvis, Laura Climent and Alejandro Arbelaez

"Characterizing Multi-Source Data for Effective Urban Mobility Modelling: The Case of New York City"

Tonny Rutayisire, Jun Liu, Samuel Moore and Carlos Balsas

"The Impact of CLIP Encoders and CNN Architectures on Model Efficiency: A Case Study on Hate Speech Detection"

Christof Kälin, Ellen Rushe, Stefan Kull and Andrew McCarren

"Autonomous Satellite Health Monitoring using EIRSAT-1 Telemetry"

James Murphy, Muhammad Deedahwar Mazhar Qureshi, Jake O'Brien and Brian Mac Namee

"A Real-Time Prediction System for Restaurant Orders Using Time Series and Behavioural Analytics: A Conceptual Framework"

Amir Arzy, Fereshteh Khodaparast and Ruairi O'Reilly

"Identifying Subject Bias in WiFi-based Human Activity Recognition"

Amany Elkelany, Robert Ross and Susan Mckeever

Keynote speaker: Eamonn Keogh

Title: The Emperor's New Algorithm: Why Most Time Series Anomaly Detection Papers Are Wrong

Abstract: Time Series Anomaly Detection (TSAD) is the task of finding unusual/anomalous/novel subsequences within a longer time series. With many potential applications in industry and science, in the last few years there has been an explosion of interest in this topic, with dozens of papers appearing each year in the top venues, such as NeurIPS, SIGKDD, VLDB, SIGMOD, PAMI etc. In this talk I will make a surprising claim, at least 95% of these papers make no contribution, because their claimed improvements are demonstrated with deeply flawed experiments that should be discounted or ignored. I will demonstrate the fallacies of these experiments with original, visually intuitive, compelling and ultimately damming examples. Having convinced the audience of my thesis, I will then move on to two more speculative questions. How did some of the top researchers in our community fail to see these issues and write such embarrassingly naïve papers, and what can be done to improve the quality of research.

"Advancing Post-OCR Correction: A Comparative Study of Synthetic Data"

Shuhao Guan and Derek Greene

"Towards AI-Driven Data Spaces: AI Catalogues to Support the EU AI Act"

Delaram Golpayegani, Harshvardhan J. Pandit and Dave Lewis

"Modeling Implicit Attitudes with Natural Language Data: A Comparison of Language Models"

Alexander Porshnev, Kevin Dirk Kiy, Diarmuid O'Donoghue, Manokamna Singh, Cai Wingfield and Dermot Lynott

"An Examination of Embedding Methods for Entity Comparison in Text-Rich Knowledge Graphs"

Huan Chen, Gareth Jones and Rob Brennan

"“An bhfuil Gaeilge agat?”: Differences in user interaction and assistant responses across languages of European origin in large-scale conversational datasets"

Aldan Creo

"Mapping Upper Secondary Computer Science Specifications Against UNESCO’s Framework of AI Learning Outcomes"

Joyce Mahon, Brian Mac Namee and Brett Becker

"NLP-Based Analysis of Annual Reports: Asset Volatility Prediction and Portfolio Strategy Application"

Xiao Li, Yang Xu, Linyi Yang, Yue Zhang and Ruihai Dong

"An Evaluation of Features Extracted from Facial Images in the Context of Accurate Age Estimation"

Malik Awais Khan, Aurelia Power, Peter Corcoran and Christina Thorpe

"Modelling Expected Threat in Gaelic Football using a Markov Chain Approach"

Ciaran Sheelan, Kevin McDaid and Jack McDonnell