Journal Articles

Chen, B and Dethlefs, N (2026) Emotionally intelligent preference optimization for conversational behavior change support, Scientific Reports, DOI: 10.1038/s41598-026-71119-8.

Rothon, C, Dethlefs, N, Houseago, R (2026) Wind turbine blade crack detection and assessment in images using machine learning, Wind Energy, 29(9), e70145, ISSN: 1095-4244. DOI: 10.1002/we.70145.

Rothon, C, Dethlefs, N, Houseago, R (2026) Wind turbine blade crack detection and assessment in images using machine learning, Wind Energy, 29(9), e70145, ISSN: 1095-4244. DOI: 10.1002/we.70145.

Sherratt, V, Elayan, S, Dethlefs, N (2026) SemioMeme: A Symbolic–Subsymbolic Knowledge Graph Dataset for Multimodal Meme Analysis, Proceedings of the International AAAI Conference on Web and Social Media, 20(1), pp.2921-2935, ISSN: 2162-3449. DOI: 10.1609/icwsm.v20i1.42792.

Sherratt, V and Dethlefs, N (2026) Clustering Internet Memes with Metric Learning and Dynamic Modality Weighting, Proceedings of the International AAAI Conference on Web and Social Media, 20(1), pp.2131-2148, ISSN: 2162-3449. DOI: 10.1609/icwsm.v20i1.42741.

Jonsson, C, Hansen, MS, Wilson, JJ, Farren, D, Dethlefs, N, Chatterjee, J, Draper, J, Donnelly, R, Dimopoulos, A, Wiens, M, Marykovskiy, Y, Barber, S (2026) Laying the foundations for context-aware and AI-ready fault diagnosis with the Operations Ontology, Journal of Physics Conference Series, 3232(1), ISSN: 1742-6588. DOI: 10.1088/1742-6596/3232/1/012005.

Bessanova, V, Tapoglou, E, Dorrell, R, Dethlefs, N, York, K (2025) Global evaluation of wave data reanalysis: Comparison of the ERA5 dataset to buoy observations, Applied Ocean Research, 157, 104490, ISSN: 0141-1187. DOI: 10.1016/j.apor.2025.104490.

Walker, C, Rothon, C, Aslansefat, K, Papadopoulos, Y, Dethlefs, N (2024) Using Large Language Models to Recommend Repair Actions for Offshore Wind Maintenance, Journal of Physics Conference Series, 2875(1), p.012025, ISSN: 1742-6588. DOI: 10.1088/1742-6596/2875/1/012025.

Dethlefs, N and Cuayahuitl, H (2024) User Engagement Triggers in Social Media Discourse on Biodiversity Conservation, ACM Transactions on Social Computing, 7(1-4), pp.1-32, ISSN: 2469-7818. DOI: 10.1145/3662685.

Tuton, E, Ma, X, Dethlefs, N (2024) Redefining Digital Twins – A Wind Energy Operations and Maintenance Perspective, Journal of Physics Conference Series, 2767(5), p.052001, ISSN: 1742-6588. DOI: 10.1088/1742-6596/2767/5/052001.

Bryan-Smith, L, Godsall, J, George, F, Egode, K, Dethlefs, N, Parsons, D (2023) Real-time social media sentiment analysis for rapid impact assessment of floods, Computers and Geosciences, 178, 105405, ISSN: 0098-3004. DOI: 10.1016/j.cageo.2023.105405.

Chatterjee, J and Dethlefs, N (2023) This new conversational AI model can be your friend, philosopher, and guide .. and even your worst enemy, Patterns, 4(1), pp.100676-100676, ISSN: 2666-3899. DOI: 10.1016/j.patter.2022.100676.

Tuton, E, Ma, X, Dethlefs, N (2023) Intelligent digital twin – machine learning system for real-time wind turbine wind speed and power generation forecasting, E3S Web of Conferences, 433, p.01008, ISSN: 2555-0403. DOI: 10.1051/e3sconf/202343301008.

Chatterjee, J, Alvela Nieto, MT, Gelbhardt, H, Dethlefs, N, Ohlendorf, J-H, Greulich, A, Thoben, K-D (2023) Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning, Environmental Data Science, 2, ISSN: 2634-4602. DOI: 10.1017/eds.2023.9.

Chatterjee, J and Dethlefs, N (2022) Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines, IEEE Access, 10, pp.84710-84737, DOI: 10.1109/access.2022.3197167.

Chatterjee, J and Dethlefs, N (2022) Facilitating a smoother transition to renewable energy with AI, Patterns, 3(6), p.100528, ISSN: 2666-3899. DOI: 10.1016/j.patter.2022.100528.

Dagtekin, O and Dethlefs, N (2022) Modelling Phytoplankton Behaviour in the North and Irish Sea with Transformer Networks, Proceedings of the Northern Lights Deep Learning Workshop, 3, ISSN: 2703-6928. DOI: 10.7557/18.6229.

Chatterjee, J and Dethlefs, N (2021) Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future, Renewable and Sustainable Energy Reviews, 144, pp.111051-111051, ISSN: 1364-0321. DOI: 10.1016/j.rser.2021.111051.

Dethlefs, N, Schoene, A, Cuayáhuitl, H (2021) A divide-and-conquer approach to neural natural language generation from structured data, Neurocomputing, 433, pp.300-309, ISSN: 0925-2312. DOI: 10.1016/j.neucom.2020.12.083.

Schoene, AM, Turner, AP, De Mel, G, Dethlefs, N (2021) Hierarchical Multiscale Recurrent Neural Networks for Detecting Suicide Notes, IEEE Transactions on Affective Computing, 14(1), pp.153-164, DOI: 10.1109/taffc.2021.3057105.

Chatterjee, J and Dethlefs, N (2020) Temporal Causal Inference in Wind Turbine SCADA Data Using Deep Learning for Explainable AI, Journal of Physics Conference Series, 1618(2), p.022022, ISSN: 1742-6588. DOI: 10.1088/1742-6596/1618/2/022022.

Chatterjee, J and Dethlefs, N (2020) Deep learning with knowledge transfer for explainable anomaly prediction in wind turbines, Wind Energy, 23(8), pp.1693-1710, ISSN: 1095-4244. DOI: 10.1002/we.2510.

Dethlefs, N, Milders, M, Cuayáhuitl, H, Al-Salkini, T, Douglas, L (2017) A natural language-based presentation of cognitive stimulation to people with dementia in assistive technology: A pilot study, Informatics for Health and Social Care, 42(4), pp.349-360, ISSN: 1753-8157. DOI: 10.1080/17538157.2016.1255627.

Dethlefs, N (2017) Domain Transfer for Deep Natural Language Generation from Abstract Meaning Representations, IEEE Computational Intelligence Magazine, 12(3), pp.18-28, ISSN: 1556-603X. DOI: 10.1109/mci.2017.2708558.

Dethlefs, N, Hastie, H, Cuayáhuitl, H, Yu, Y, Rieser, V, Lemon, O (2016) Information density and overlap in spoken dialogue, Computer Speech & Language, 37, pp.82-97, ISSN: 0885-2308. DOI: 10.1016/j.csl.2015.11.001.

DETHLEFS, N and CUAYÁHUITL, H (2015) Hierarchical reinforcement learning for situated natural language generation, Natural Language Engineering, 21(3), pp.391-435, ISSN: 1351-3249. DOI: 10.1017/s1351324913000375.

Cuayáhuitl, H, Kruijff-Korbayová, I, Dethlefs, N (2014) Nonstrict Hierarchical Reinforcement Learning for Interactive Systems and Robots, ACM Transactions on Interactive Intelligent Systems, 4(3), pp.1-30, ISSN: 2160-6455. DOI: 10.1145/2659003.

Cuayáhuitl, H, Frommberger, L, Dethlefs, N, Raux, A, Marge, M, Zender, H (2014) Introduction to the Special Issue on Machine Learning for Multiple Modalities in Interactive Systems and Robots, ACM Transactions on Interactive Intelligent Systems, 4(3), pp.1-6, ISSN: 2160-6455. DOI: 10.1145/2670539.

Dethlefs, N (2014) Context‐Sensitive Natural Language Generation: From Knowledge‐Driven to Data‐Driven Techniques, Language and Linguistics Compass, 8(3), pp.99-115, ISSN: 1749-818X. DOI: 10.1111/lnc3.12067.

Dethlefs, N, Wu, Y, Kazerani, A, Winter, S (2011) Generation of Adaptive Route Descriptions in Urban Environments, Spatial Cognition and Computation, 11(2), pp.153-177, ISSN: 1387-5868. DOI: 10.1080/13875868.2010.525272.

Cuayáhuitl, H and Dethlefs, N (2011) Spatially-aware dialogue control using hierarchical reinforcement learning, ACM Transactions on Speech and Language Processing, 7(3), pp.1-26, ISSN: 1550-4875. DOI: 10.1145/1966407.1966410.

Tenbrink, T, Ross, RJ, Thomas, KE, Dethlefs, N, Andonova, E (2010) Route instructions in map-based human–human and human–computer dialogue: A comparative analysis, Journal of Computer Languages, 21(5), pp.292-309, ISSN: 2665-9182. DOI: 10.1016/j.jvlc.2010.07.001.

Conferences

Dogan, S, Dethlefs, N, Chakraborty, D (2026) Early Multimodal Prediction of Cross-Lingual Meme Virality on Reddit: A Time-Window Analysis. In WebSci '26: 18th ACM Web Science Conference 2026, Proceedings of the 18th ACM Web Science Conference 2026, pp.86-96, DOI: 10.1145/3795766.3799745.

Wuraola, I, Marciniak, D, Dethlefs, N (2026) SLANG-GraphRAG: Multi-Layered Retrieval with Domain-Specific Knowledge for Low Resource Social Media Conversations. In Findings of the Association for Computational Linguistics: EACL 2026, 19th Conference of the European Chapter of the Association for Computational Linguistics Findings of Eacl 2026, Rabat, Morocco, pp.3919-3931, DOI: 10.18653/v1/2026.findings-eacl.203.

Rothon, C, Walker, C, Aslansefat, K, Dethlefs, N, Papadopoulos, Y (2024) Safety Monitoring for Large Language Models: A Case Study of Offshore Wind Maintenance. In Safe AI Systems,, DOI: 10.65391/r1929.

Wuraola, I, Dethlefs, N, Marciniak, D (2024) Understanding Slang with LLMs: Modelling Cross-Cultural Nuances through Paraphrasing. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp.15525-15531, DOI: 10.18653/v1/2024.emnlp-main.869.

Sherratt, V, Dogan, S, Wuraola, I, Bryan-smith, L, Onwuchekwa, O, Dethlefs, N (2024) BDA at SemEval-2024 Task 4: Detection of Persuasion in Memes Across Languages with Ensemble Learning and External Knowledge. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pp.123-132, DOI: 10.18653/v1/2024.semeval-1.20.

Sherratt, V, Pimbblet, K, Dethlefs, N (2023) Multi-channel Convolutional Neural Network for Precise Meme Classification. In ICMR '23: International Conference on Multimedia Retrieval, Proceedings of the 2023 ACM International Conference on Multimedia Retrieval, pp.190-198, DOI: 10.1145/3591106.3592275.

Dagtekin, O and Dethlefs, N (2022) Imputation of Partially Observed Water Quality Data Using Self-Attention LSTM. In 2022 International Joint Conference on Neural Networks (IJCNN), pp.1-8, DOI: 10.1109/ijcnn55064.2022.9892446.

Schoene, AM, Dethlefs, N, Ananiadou, S (2022) RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification. In Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022), pp.6317-6327, DOI: 10.63317/2uz8zds4txxh.

Chatterjee, J and Dethlefs, N (2020) A Dual Transformer Model for Intelligent Decision Support for Maintenance of Wind Turbines. In 2020 International Joint Conference on Neural Networks (IJCNN), pp.1-10, DOI: 10.1109/ijcnn48605.2020.9206839.

Lacey, G, Schoene, A, Dethlefs, N, Turner, A (2020) Improving the Transparency of Deep Neural Networks using Artificial Epigenetic Molecules. In , International Joint Conference on Computational Intelligence, pp.167-175, DOI: 10.5220/0010105301670175.

Lacey, G, Schoene, A, Dethlefs, N, Turner, A (2020) Improving the transparency of deep neural networks using artificial epigenetic molecules. In , Ijcci 2020 Proceedings of the 12th International Joint Conference on Computational Intelligence, pp.167-175.

Lacey, G, Schoene, A, Dethlefs, N, Turner, A (2019) Modularity Within Artificial Gene Regulatory Networks. In 2019 IEEE Congress on Evolutionary Computation (CEC), pp.731-738, DOI: 10.1109/cec.2019.8789911.

Schoene, AM, Lacey, G, Turner, AP, Dethlefs, N (2019) Dilated LSTM with attention for Classification of Suicide Notes. In Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019), pp.136-145, DOI: 10.18653/v1/d19-6217.

Dethlefs, N and Hawick, K (2017) DEFIne. In Proceedings of the 2nd International Workshop on Real World Domain Specific Languages, pp.1-10, DOI: 10.1145/3039895.3039898.

Schoene, AM and Dethlefs, N (2016) Automatic Identification of Suicide Notes from Linguistic and Sentiment Features. In Proceedings of the 10th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities, pp.128-133, DOI: 10.18653/v1/w16-2116.

Cuayahuiti, H, Dethlefs, N, Hastie, H, Liu, X (2014) Training a Statistical Surface Realiser from Automatic Slot Labelling. In 2014 IEEE Spoken Language Technology Workshop (SLT), pp.112-117, DOI: 10.1109/slt.2014.7078559.

Cuayáhuitl, H, Dethlefs, N, Hastie, H (2014) A Semi-Supervised Clustering Approach for Semantic Slot Labelling. In 2014 13th International Conference on Machine Learning and Applications, pp.500-505, DOI: 10.1109/icmla.2014.87.

Hastie, H, Aufaure, M-A, Alexopoulos, P, Bouchard, H, Breslin, C, Cuayáhuitl, H, Dethlefs, N, Gašić, M, Henderson, J, Lemon, O, Liu, X, Mika, P, Ben Mustapha, N, Potter, T, Rieser, V, Thomson, B, Tsiakoulis, P, Vanrompay, Y, Villazon-Terrazas, B, Yazdani, M, Young, S, Yu, Y (2014) The PARLANCE mobile application for interactive search in English and Mandarin. In Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), pp.260-262, DOI: 10.18653/v1/w14-4336.

Hastie, H, Aufaure, M-A, Alexopoulos, P, Bouchard, H, Breslin, C, Cuayáhuitl, H, Dethlefs, N, Gašić, M, Henderson, J, Lemon, O, Liu, X, Mika, P, Mustapha, NB, Potter, T, Rieser, V, Thomson, B, Tsiakoulis, P, Vanrompay, Y, Villazon-Terrazas, B, Yazdani, M, Young, S, Yu, Y (2014) The PARLANCE mobile application for interactive search in English and Mandarin. In Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), pp.260-262, DOI: 10.3115/v1/w14-4336.

Dethlefs, N, Cuayáhuitl, H, Hastie, H, Rieser, V, Lemon, O (2014) Cluster-based Prediction of User Ratings for Stylistic Surface Realisation. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp.702-711, DOI: 10.3115/v1/e14-1074.

Cuaydáhuitl, H, Dethlefs, N, Hastie, H, Lemon, O (2013) BARGE-IN EFFECTS IN BAYESIAN DIALOGUE ACT RECOGNITION AND SIMULATION. In 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, pp.102-107, DOI: 10.1109/asru.2013.6707713.

Cuayáhuitl, H, van Otterlo, M, Dethlefs, N, Frommberger, L (2013) Machine learning for interactive systems and robots. In Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication, pp.19-28, DOI: 10.1145/2493525.2493530.

Cuayáhuitl, H and Dethlefs, N (2011) Optimizing situated dialogue management in unknown environments. In Interspeech 2011, pp.1009-1012, DOI: 10.21437/interspeech.2011-298.

Books

Dethlefs, N and Chatterjee, J (2025) Renewable Energy Transition with Artificial Intelligence: Challenge-driven Solutions. DOI: 10.1002/9781394300068.

Chapters

Houseago, RC, Mockute, A, Cross, EJ, Dethlefs, N (2023) Rapid Assessment of Offshore Monopile Fatigue Using Machine Learning. In Lecture Notes in Civil Engineering, Springer International Publishing, pp.101-112, ISBN: 9783031072536. DOI: 10.1007/978-3-031-07254-3_11.

Walker, C, Rothon, C, Aslansefat, K, Papadopoulos, Y, Dethlefs, N (2022) A Deep Learning Framework for Wind Turbine Repair Action Prediction Using Alarm Sequences and Long Short Term Memory Algorithms. In Model-Based Safety and Assessment, Springer Nature, pp.189-203, DOI: 10.1007/978-3-031-15842-1_14.

Chatterjee, J and Dethlefs, N (2020) Deep reinforcement learning for maintenance planning of offshore vessel transfer. In Developments in Renewable Energies Offshore, Taylor & Francis, pp.435-443, DOI: 10.1201/9781003134572-50.

Turner, AP, Lacey, G, Schoene, A, Dethlefs, N (2019) Evolutionary Constraint in Artificial Gene Regulatory Networks. In Advances in Intelligent Systems and Computing, Springer International Publishing, pp.29-40, ISBN: 9783319979816. DOI: 10.1007/978-3-319-97982-3_3.

Dethlefs, N and Turner, A (2017) Deep Text Generation – Using Hierarchical Decomposition to Mitigate the Effect of Rare Data Points. In Language, Data, and Knowledge, Springer Nature, pp.290-298, DOI: 10.1007/978-3-319-59888-8_25.

Hastie, H, Cuayáhuitl, H, Dethlefs, N, Keizer, S, Liu, X (2017) Extrinsic Versus Intrinsic Evaluation of Natural Language Generation for Spoken Dialogue Systems and Social Robotics. In Dialogues with Social Robots, Springer Nature, pp.303-311, DOI: 10.1007/978-981-10-2585-3_24.

Dethlefs, N and Cuayáhuitl, H (2014) A joint learning approach for situated language generation. In Natural Language Generation in Interactive Systems, Cambridge University Press (CUP), pp.180-204, DOI: 10.1017/cbo9780511844492.008.

Cuayáhuitl, H, Dethlefs, N, Frommberger, L, Richter, K-F, Bateman, J (2010) Generating Adaptive Route Instructions Using Hierarchical Reinforcement Learning. In Spatial Cognition VII, Springer Nature, pp.319-334, DOI: 10.1007/978-3-642-14749-4_27.