Vertex Clustering of Augmented Graph Streams. - Ryan McConville; Weiru Liu; Paul Miller 003 (SDM, 2015)

Accelerating large scale centroid-based clustering with locality sensitive hashing. - Ryan McConville; Xin Cao 001; Weiru Liu; Paul Miller 003 (ICDE, 2016)

Vertex Deduplication Based on String Similarity and Community Membership. - Ryan McConville; Weiru Liu; Jun Hong 001 (COMPLEX NETWORKS, 2017)

SPHERE in a Box: Practical and Scalable EurValve Activity Monitoring Smart Home Kit. - James Pope; Ryan McConville; Michal Kozlowski; Xenofon Fafoutis; Raúl Santos-Rodríguez; Robert J. Piechocki; Ian Craddock (LCN Workshops, 2017)

Clustering algorithms for large scale graph data. - Ryan McConville (2017)

Person Identification and Discovery With Wrist Worn Accelerometer Data. - Ryan McConville; Raúl Santos-Rodríguez; Niall Twomey (ESANN, 2018)

On-Board Feature Extraction from Acceleration Data for Activity Recognition. - Atis Elsts; Ryan McConville; Xenofon Fafoutis; Niall Twomey; Robert J. Piechocki; Raúl Santos-Rodriguez; Ian Craddock (EWSN, 2018)

Proper Losses for Learning with Example-Dependent Costs. - Alexander Hepburn; Ryan McConville; Raúl Santos-Rodríguez; Jesús Cid-Sueiro; Dario García-García (LIDTA@ECML/PKDD, 2018)

Understanding the quality of calibrations for indoor localisation. - Ryan McConville; Dallan Byrne; Ian Craddock; Robert J. Piechocki; James Pope; Raúl Santos-Rodríguez (WF-IoT, 2018)

Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable. - Ryan McConville; Gareth Archer; Ian Craddock; Herman J. ter Horst; Robert J. Piechocki; James Pope; Raúl Santos-Rodriguez (CoRR, 2018)

Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks. - Michal Kozlowski; Ryan McConville; Raúl Santos-Rodríguez; Robert J. Piechocki (CoRR, 2018)

A Comprehensive Study of Activity Recognition Using Accelerometers. - Niall Twomey; Tom Diethe; Xenofon Fafoutis; Atis Elsts; Ryan McConville; Peter A. Flach; Ian Craddock (Informatics, 2018)

Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback. - Taku Yamagata; Raúl Santos-Rodríguez; Ryan McConville; Atis Elsts (CoRR, 2019)

Low Cost Localisation in Residential Environments using High Resolution CIR Information. - Mohammud Junaid Bocus; Jonas Paulavicius; Ryan McConville; Raúl Santos-Rodríguez; Robert J. Piechocki (GLOBECOM, 2020)

Perceptnet: A Human Visual System Inspired Neural Network For Estimating Perceptual Distance. - Alexander Hepburn; Valero Laparra; Jesús Malo; Ryan McConville; Raúl Santos-Rodríguez (ICIP, 2020)

Translation Resilient Opportunistic WiFi Sensing. - Mohammud Junaid Bocus; Wenda Li 002; Jonas Paulavicius; Ryan McConville; Raúl Santos-Rodríguez; Kevin Chetty; Robert J. Piechocki (ICPR, 2020)

N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding. - Ryan McConville; Raúl Santos-Rodríguez; Robert J. Piechocki; Ian Craddock (ICPR, 2020)

Enforcing perceptual consistency on Generative Adversarial Networks by using the Normalised Laplacian Pyramid Distance. - Alexander Hepburn; Valero Laparra; Ryan McConville; Raúl Santos-Rodríguez (NLDL, 2020)

ImRec: Learning Reciprocal Preferences Using Images. - James Neve; Ryan McConville (RecSys, 2020)

Social Network Influence Ranking via Embedding Network Interactions for User Recommendation. - Hongbo Bo; Ryan McConville; Jun Hong 001; Weiru Liu (WWW (Companion Volume), 2020)

Energy-efficient activity recognition framework using wearable accelerometers. - Atis Elsts; Niall Twomey; Ryan McConville; Ian Craddock (J. Netw. Comput. Appl., 2020)

Social Influence Prediction with Train and Test Time Augmentation for Graph Neural Networks. - Hongbo Bo; Ryan McConville; Jun Hong 001; Weiru Liu (IJCNN, 2021)

Data labelling in the wild: annotating free-living activities and Parkinson's disease symptoms. - Catherine Morgan; Farnoosh Heidarivincheh; Ian Craddock; Ryan McConville; Miquel Perelló-Nieto; Emma L. Tonkin; Alessandro Masullo; Antonis Vafeas; Mickey Kim; Roisin McNaney; Gregory J. L. Tourte; Alan L. Whone (PerCom Workshops, 2021)

Container Escape Detection for Edge Devices. - James Pope; Francesco Raimondo; Vijay Kumar; Ryan McConville; Robert J. Piechocki; George Oikonomou; Thomas Pasquier; Bo Luo; Dan Howarth; Ioannis Mavromatis; Pietro Edoardo Carnelli; Adrián Sánchez-Mompó; et al. (SenSys, 2021)

Photos Are All You Need for Reciprocal Recommendation in Online Dating. - James Neve; Ryan McConville (CoRR, 2021)

Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills. - Taku Yamagata; Ryan McConville; Raúl Santos-Rodríguez (CoRR, 2021)

Vesta: A digital health analytics platform for a smart home in a box. - Ryan McConville; Gareth Archer; Ian Craddock; Michal Kozlowski; Robert J. Piechocki; James Pope; Raúl Santos-Rodríguez (Future Gener. Comput. Syst., 2021)

Multimodal Classification of Parkinson's Disease in Home Environments with Resiliency to Missing Modalities. - Farnoosh Heidarivincheh; Ryan McConville; Catherine Morgan; Roisin McNaney; Alessandro Masullo; Majid Mirmehdi; Alan L. Whone; Ian Craddock (Sensors, 2021)

Exploring Perceptions of Cross-Sectoral Data Sharing with People with Parkinson's. - Roisin McNaney; Catherine Morgan; Pranav Kulkarni; Julio Vega; Farnoosh Heidarivincheh; Ryan McConville; Alan L. Whone; Mickey Kim; Reuben Kirkham; Ian Craddock (CHI, 2022)

IoT Key Exchange Performance Analysis. - Francesco Raimondo; Ufuk Erol; Samuel Gunner; James Pope; Robert Zakrzewski; Mike Faulks; Ryan McConville; Thomas Pasquier; Robert J. Piechocki; George Oikonomou (EWSN, 2022)

Self-Supervised WiFi-Based Activity Recognition. - Mohammud Junaid Bocus; Hok-Shing Lau; Ryan McConville; Robert J. Piechocki; Raúl Santos-Rodríguez (GLOBECOM (Workshops), 2022)

Temporal Self-Supervised Learning for RSSI-based Indoor Localization. - Jonas Paulavicius; Seifallah Jardak; Ryan McConville; Robert J. Piechocki; Raúl Santos-Rodríguez (ICC, 2022)

Explainable AI for Non-Experts: Energy Tariff Forecasting. - Hongnan Ma; Kevin McAreavey; Ryan McConville; Weiru Liu (ICAC, 2022)

Ego-graph Replay based Continual Learning for Misinformation Engagement Prediction. - Hongbo Bo; Ryan McConville; Jun Hong 001; Weiru Liu (IJCNN, 2022)

Radio signal strength indication augmentation for one-shot learning in indoor localisation. - Thanaphon Suwannaphong; Ryan McConville; Ian Craddock (SmartWear@MobiCom, 2022)

MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset. - Dan Saattrup Nielsen; Ryan McConville (SIGIR, 2022)

Multimodal Indoor Localisation for Measuring Mobility in Parkinson's Disease using Transformers. - Ferdian Jovan; Ryan McConville; Catherine Morgan; Emma Tonkin; Alan L. Whone; Ian Craddock (CoRR, 2022)

Addressing contingency in algorithmic misinformation detection: Toward a responsible innovation agenda. - Andrés Domínguez Hernández; Richard Owen; Dan Saattrup Nielsen; Ryan McConville (CoRR, 2022)

Resource-Interaction Graph: Efficient Graph Representation for Anomaly Detection. - James Pope; Jinyuan Liang; Vijay Kumar; Francesco Raimondo; Xinyi Sun; Ryan McConville; Thomas Pasquier; Robert J. Piechocki; George Oikonomou; Bo Luo; Dan Howarth; Ioannis Mavromatis; et al. (CoRR, 2022)

Outdoor Localization Using BLE RSSI and Accessible Pedestrian Signals for the Visually Impaired at Intersections. - Ki-Young Shin; Ryan McConville; Oussama Metatla; Min Hye Chang; Chiyoung Han; Junhaeng Lee; Anne Roudaut (Sensors, 2022)

Self-supervised multimodal fusion transformer for passive activity recognition. - Armand K. Koupai; Mohammud Junaid Bocus; Raúl Santos-Rodríguez; Robert J. Piechocki; Ryan McConville (IET Wirel. Sens. Syst., 2022)

Predicting Interpersonal Influence from Conversational Features. - Luke Gassmann; Ryan McConville; Matthew Edwards 001 (BESC, 2023)

Uncertainty in GNN Learning Evaluations: The Importance of a Consistent Benchmark for Community Detection. - William Leeney; Ryan McConville (COMPLEX NETWORKS (1), 2023)

A Comparative Analysis of Information Cascade Prediction Using Dynamic Heterogeneous and Homogeneous Graphs. - Yiwen Wu; Kevin McAreavey; Weiru Liu; Ryan McConville (COMPLEX NETWORKS (4), 2023)

Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda. - Andrés Domínguez Hernández; Richard Owen; Dan Saattrup Nielsen; Ryan McConville (FAccT, 2023)

Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting. - Ferdian Jovan; Catherine Morgan; Ryan McConville; Emma L. Tonkin; Ian Craddock; Alan L. Whone (KDD, 2023)

What Will Make Misinformation Spread: An XAI Perspective. - Hongbo Bo; Yiwen Wu; Zinuo You; Ryan McConville; Jun Hong 001; Weiru Liu (xAI (2), 2023)

Characterizing Discourse and Engagement Across Topics of Misinformation on Twitter. - Dominika Nadia Wojtczak; Claudia Peersman; Luisa Zuccolo; Ryan McConville (IEEE Access, 2023)

Search for the UGLE Truth: An Investigation into Unsupervised GNN Learning Environments. - Will Leeney; Ryan McConville (CoRR, 2023)

Privacy in Multimodal Federated Human Activity Recognition. - Alex Iacob; Pedro Porto Buarque de Gusmão; Nicholas D. Lane; Armand K. Koupai; Mohammud Junaid Bocus; Raúl Santos-Rodríguez; Robert J. Piechocki; Ryan McConville (CoRR, 2023)

The Safety Challenges of Deep Learning in Real-World Type 1 Diabetes Management. - Harry Emerson; Ryan McConville; Matthew Guy (CoRR, 2023)

A Framework for Exploring Federated Community Detection. - William Leeney; Ryan McConville (CoRR, 2023)

Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes. - Harry Emerson; Matthew Guy; Ryan McConville (J. Biomed. Informatics, 2023)

Leading the Mastodon Herd: Analysing the Traits of Influential Leaders on a Decentralised Social Media Platform. - Luke Gassmann; Ryan McConville; Matthew Edwards 001 (IEEE Big Data, 2024)

Unsupervised Optimisation of GNNs for Node Clustering. - William Leeney; Ryan McConville (CoRR, 2024)

Optimising TinyML with Quantization and Distillation of Transformer and Mamba Models for Indoor Localisation on Edge Devices. - Thanaphon Suwannaphong; Ferdian Jovan; Ian Craddock; Ryan McConville (CoRR, 2024)

Transfer Learning of RSSI to Improve Indoor Localisation Performance. - Thanaphon Suwannaphong; Ryan McConville; Ian Craddock (CoRR, 2024)

Uncertainty in GNN Learning Evaluations: A Comparison between Measures for Quantifying Randomness in GNN Community Detection. - William Leeney; Ryan McConville (Entropy, 2024)

Lightweight Decentralized Neural Network-Based Strategies for Multi-Robot Patrolling. - James C. Ward; Ryan McConville; Edmund R. Hunt (SAC, 2025)

Federated Mental Wellbeing Assessment Using Smartphone Sensors Under Unreliable Participation. - Gavryel Martis; Ryan McConville (IEEE Access, 2025)

Flexible Blood Glucose Control: Offline Reinforcement Learning from Human Feedback. - Harry Emerson; Sam Gordon James; Matthew Guy; Ryan McConville (CoRR, 2025)