| Deep reinforcement learning: an overview SS Mousavi, M Schukat, E Howley Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016: Volume …, 2018 | 428 | 2018 |
| Traffic light control using deep policy‐gradient and value‐function‐based reinforcement learning SS Mousavi, M Schukat, E Howley IET Intelligent Transport Systems 11 (7), 417-423, 2017 | 363 | 2017 |
| Deep reinforcement learning for home energy management system control P Lissa, C Deane, M Schukat, F Seri, M Keane, E Barrett Energy and AI 3, 100043, 2021 | 120 | 2021 |
| A ZigBee honeypot to assess IoT cyberattack behaviour S Dowling, M Schukat, H Melvin 2017 28th Irish signals and systems conference (ISSC), 1-6, 2017 | 91 | 2017 |
| Unintended consequences of wearable sensor use in healthcare M Schukat, D McCaldin, K Wang, G Schreier, NH Lovell, M Marschollek, ... Yearbook of medical informatics 25 (01), 73-86, 2016 | 70 | 2016 |
| Public key infrastructures and digital certificates for the Internet of things M Schukat, P Cortijo 2015 26th Irish signals and systems conference (ISSC), 1-5, 2015 | 51 | 2015 |
| Classification of ECG arrhythmia using learning vector quantization neural networks AM Elsayad 2009 International Conference on Computer Engineering & Systems, 139-144, 2009 | 47 | 2009 |
| Portable medical monitoring and diagnostic system D Chambers, G Lyons, M Madden, M Schukat US Patent App. 11/658,629, 2009 | 40 | 2009 |
| Arrhythmia identification from ECG signals with a neural network classifier based on a Bayesian framework D Gao, M Madden, M Schukat, D Chambers, G Lyons Proceedings of the 24th SGAI International Conference on Innovative …, 2004 | 40 | 2004 |
| Arrhythmia identification from ECG signals with a neural network classifier based on a Bayesian framework D Gao, M Madden, M Schukat, D Chambers, G Lyons Proceedings of the 24th SGAI International Conference on Innovative …, 2004 | 40 | 2004 |
| Learning to predict where to look in interactive environments using deep recurrent q-learning S Mousavi, M Schukat, E Howley, A Borji, N Mozayani arXiv preprint arXiv:1612.05753, 2016 | 37 | 2016 |
| Using reinforcement learning to conceal honeypot functionality S Dowling, M Schukat, E Barrett Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019 | 34 | 2019 |
| Authentication using virtual certificate authorities: A new security paradigm for wireless sensor networks E Holohan, M Schukat 2010 Ninth IEEE International Symposium on Network Computing and …, 2010 | 34 | 2010 |
| Improving adaptive honeypot functionality with efficient reinforcement learning parameters for automated malware S Dowling, M Schukat, E Barrett Journal of Cyber Security Technology 2 (2), 75-91, 2018 | 32 | 2018 |
| Peer to peer authentication for small embedded systems: A zero-knowledge-based approach to security for the Internet of Things P Flood, M Schukat The 10th International Conference on Digital Technologies 2014, 68-72, 2014 | 31 | 2014 |
| Transfer learning applied to reinforcement learning-based hvac control P Lissa, M Schukat, E Barrett SN Computer Science 1 (3), 127, 2020 | 26 | 2020 |
| Transfer learning applied to DRL-Based heat pump control to leverage microgrid energy efficiency P Lissa, M Schukat, M Keane, E Barrett Smart Energy 3, 100044, 2021 | 25 | 2021 |
| Precision time protocol attack strategies and their resistance to existing security extensions W Alghamdi, M Schukat Cybersecurity 4, 1-17, 2021 | 24 | 2021 |
| An enhanced sum rate in the cluster based cognitive radio relay network using the sequential approach for the future Internet of Things MS Miah, M Schukat, E Barrett Human-centric Computing and Information Sciences 8, 1-27, 2018 | 24 | 2018 |
| Sensing and throughput analysis of a MU-MIMO based cognitive radio scheme for the Internet of Things MS Miah, M Schukat, E Barrett Computer Communications 154, 442-454, 2020 | 23 | 2020 |
Enda HowleyAssociate Professor in Computer Science, University of GalwayVerified email at nuigalway.ie
