| 2026 | ICTIR | RAMP: Robust Ad Recommendation Under Limited Personalized-Feature Availability via Masking and Alignment Pathways. | Dairui Liu, Zhongyi Lu, Roger Zhe Li, Changhong Jin, Jitao Lu, Xinyang Shao, Bichen Shi, Mete Sertkan, Aghiles Salah, Aonghus Lawlor, Barry Smyth, Tri Kurniawan Wijaya, Ruihai Dong, Xingsheng Guo |
| 2026 | WSDM | Transfer Learning via User-Item Graph Convolution for Enhanced Cross-Domain Recommendation. | Zheng Ju, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Ruihai Dong, Aonghus Lawlor |
| 2025 | ECIR | DiffGR: A Discrete Diffusion-Based Model for Personalised Recommendation by Reconstructing User-Item Bipartite Graphs. | Zheng Ju, Honghui Du, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor |
| 2025 | ICDM | Multi-Label Transfer Learning in Non-Stationary Data Streams. | Honghui Du, Leandro L. Minku, Aonghus Lawlor, Huiyu Zhou |
| 2025 | IJCNN | Is Complete Labeling Necessary? Understanding Active Learning in Longitudinal Medical Imaging. | Siteng Ma, Honghui Du, Prateek Mathur, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor, Ruihai Dong |
| 2025 | MICCAI | Spatial Aggregation for Semi-supervised Active Learning in 3D Medical Image Segmentation. | Siteng Ma, Honghui Du, Dairui Liu, Kathleen M. Curran, Aonghus Lawlor, Ruihai Dong |
| 2025 | MICCAI | Lesion-Aware CT-to-MRI Synthesis Using a Mask-Informed Diffusion with Adaptive-Weighted Loss (MIDAS). | Prateek Mathur, Paul Banahan, Jane Burns, Peter MacMahon, Aonghus Lawlor |
| 2025 | RecSys | EARL: The 2nd Workshop on Evaluating and Applying Recommender Systems with Large Language Models. | Irene Li, Ruihai Dong, Guillaume Salha-Galvan, Aonghus Lawlor, Dairui Liu, Lei Li |
| 2025 | RecSys | SlateLLM: Distilling LLM Semantics into Session-Aware Slate Recommendation without Inference Overhead. | Aayush Singha Roy, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley |
| 2025 | SIGIR | NodeRec+: A Lightweight Framework for Federated Recommender Systems. | Diarmuid O'Reilly-Morgan, Erika Duriakova, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor |
| 2025 | VCIP | SplitFedEE: Balancing Communication and Accuracy. | Erika Duriakova, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor |
| 2024 | ACCV | CleftLipGAN : Interactive GAN-Inpainting for Post-Operative Cleft Lip Reconstruction. | Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor |
| 2024 | ADBIS | Entity Matching with Large Language Models as Weak and Strong Labellers. | Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Erika Duriakova, Honghui Du, Neil Hurley, Aonghus Lawlor |
| 2024 | CIKM | RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models. | Dairui Liu, Boming Yang, Honghui Du, Derek Greene, Neil Hurley, Aonghus Lawlor, Ruihai Dong, Irene Li |
| 2024 | ICASSP | Breaking the Barrier: Selective Uncertainty-Based Active Learning for Medical Image Segmentation. | Siteng Ma, Haochang Wu, Aonghus Lawlor, Ruihai Dong |
| 2024 | ICCBR | A Case-Based Reasoning Approach to Post-injury Training Recommendations for Marathon Runners. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2024 | ICPRAM | Enhancing Surgical Visualization: Feasibility Study on GAN-Based Image Generation for Post Operative Cleft Palate Images. | Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor |
| 2024 | ICPRAM | Towards Objective Assessment of Cleft Surgical Outcomes: A GAN-Inpainting Based Approach. | Daniel Anojan Atputharuban, Christoph Theopold, Aonghus Lawlor |
| 2024 | MICCAI | Adaptive Curriculum Query Strategy for Active Learning in Medical Image Classification. | Siteng Ma, Honghui Du, Kathleen M. Curran, Aonghus Lawlor, Ruihai Dong |
| 2024 | MICCAI | Tracking Lesion Evolution Using a Boundary Enhanced Approach for MS Change Segmentation (BEAMS). | Prateek Mathur, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor |
| 2024 | RecSys | Recommending Personalised Targeted Training Adjustments for Marathon Runners. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2024 | RecSys | Exploring Coresets for Efficient Training and Consistent Evaluation of Recommender Systems. | Zheng Ju, Honghui Du, Elias Z. Tragos, Neil Hurley, Aonghus Lawlor |
| 2024 | SGAI | Using Pseudo Cases and Stratified Case-Based Reasoning to Generate and Evaluate Training Adjustments for Marathon Runners. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2023 | CVPR | FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks. | Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor, Kathleen M. Curran |
| 2023 | ECIR | Item Graph Convolution Collaborative Filtering for Inductive Recommendations. | Edoardo D'Amico, Khalil Muhammad, Elias Z. Tragos, Barry Smyth, Neil Hurley, Aonghus Lawlor |
| 2023 | FlAIRS | Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. | Aayush Singha Roy, Edoardo D'Amico, Aonghus Lawlor, Neil Hurley |
| 2023 | ICONIP | Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated Cases. | Haiwen Du, Zheng Ju, Yu An, Honghui Du, Dongjie Zhu, Zhaoshuo Tian, Aonghus Lawlor, Ruihai Dong |
| 2023 | IJCAI | Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework. | Elias Z. Tragos, Diarmuid O'Reilly-Morgan, James Geraci, Bichen Shi, Barry Smyth, Cailbhe Doherty, Aonghus Lawlor, Neil Hurley |
| 2023 | ICPRAM | Adaptive Adversarial Samples Based Active Learning for Medical Image Classification. | Siteng Ma, Yu An, Jing Wang, Aonghus Lawlor, Ruihai Dong |
| 2023 | PAKDD | Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. | Edoardo D'Amico, Aonghus Lawlor, Neil Hurley |
| 2023 | RecSys | Scalable Deep Q-Learning for Session-Based Slate Recommendation. | Aayush Singha Roy, Edoardo D'Amico, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley |
| 2022 | ICCBR | An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2022 | ICWE | MARF: User-Item Mutual Aware Representation with Feedback. | Qinqin Wang, Khalil Muhammad, Diarmuid O'Reilly-Morgan, Barry Smyth, Elias Z. Tragos, Aonghus Lawlor, Neil Hurley, Ruihai Dong |
| 2021 | ICCBR | A Case-Based Reasoning Approach to Predicting and Explaining Running Related Injuries. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2020 | ICCBR | Using Case-Based Reasoning to Predict Marathon Performance and Recommend Tailored Training Plans. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2020 | ICMLA | A Collaborative Filtering Approach to Successfully Completing The Marathon. | Jakim Berndsen, Barry Smyth, Aonghus Lawlor |
| 2020 | KDD | FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems. | Khalil Muhammad, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Neil Hurley, James Geraci, Aonghus Lawlor |
| 2020 | RecSys | Fit to Run: Personalised Recommendations for Marathon Training. | Jakim Berndsen, Barry Smyth, Aonghus Lawlor |
| 2020 | RecSys | Providing Explainable Race-Time Predictions and Training Plan Recommendations to Marathon Runners. | Ciara Feely, Brian Caulfield, Aonghus Lawlor, Barry Smyth |
| 2020 | RecSys | Combining Rating and Review Data by Initializing Latent Factor Models with Topic Models for Top-N Recommendation. | Francisco J. Pea, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Neil Hurley, Erika Duriakova, Barry Smyth, Aonghus Lawlor |
| 2019 | RecSys | Pace my race: recommendations for marathon running. | Jakim Berndsen, Barry Smyth, Aonghus Lawlor |
| 2019 | RecSys | PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy. | Erika Duriakova, Elias Z. Tragos, Barry Smyth, Neil Hurley, Francisco J. Pea, Panagiotis Symeonidis, James Geraci, Aonghus Lawlor |
| 2019 | RecSys | PyRecGym: a reinforcement learning gym for recommender systems. | Bichen Shi, Makbule Gulcin Ozsoy, Neil Hurley, Barry Smyth, Elias Z. Tragos, James Geraci, Aonghus Lawlor |
| 2018 | FlAIRS | A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews. | Khalil Muhammad, Aonghus Lawlor, Barry Smyth |
| 2018 | IUI | Automatic Generation of Natural Language Explanations. | Felipe Costa, Sixun Ouyang, Peter Dolog, Aonghus Lawlor |
| 2017 | ICCBR | On the Pros and Cons of Explanation-Based Ranking. | Khalil Muhammad, Aonghus Lawlor, Barry Smyth |
| 2017 | RecSys | Running with Recommendation. | Jakim Berndsen, Aonghus Lawlor, Barry Smyth |
| 2016 | FlAIRS | On the Use of Opinionated Explanations to Rank and Justify Recommendations. | Khalil Muhammad, Aonghus Lawlor, Barry Smyth |
| 2016 | IUI | A Live-User Study of Opinionated Explanations for Recommender Systems. | Khalil Ibrahim Muhammad, Aonghus Lawlor, Barry Smyth |
| 2015 | ICCBR | Great Explanations: Opinionated Explanations for Recommendations. | Khalil Muhammad, Aonghus Lawlor, Rachael Rafter, Barry Smyth |
| 2015 | SGAI | Opinionated Explanations for Recommendation Systems. | Aonghus Lawlor, Khalil Muhammad, Rachael Rafter, Barry Smyth |
| 2012 | KDD | City-scale traffic simulation from digital footprints. | Gavin McArdle, Aonghus Lawlor, Eoghan Furey, Alexei Pozdnoukhov |