Dr Noura Al Moubayed, BA MSc PhD
(email at firstname.lastname@example.org)
Dr Al Moubayed is an Assistant Professor at the department of computer science in Durham University, and a Visiting Associate Professor at the School of Computing Science in Newcastle University.
Her main research interest is in machine learning, natural language processing, and optimisation. Dr Al Moubayed obtained her PhD from the Robert Gordon University, followed by post-doctoral positions in the University of Glasgow and Durham University. She developed machine learning and deep learning solutions in the areas of healthcare, social signal processing, cyber-security, and Brain-Computer Interfaces. All of which involve high dimensional, noisy and imbalance data challenges.
Indicators of Esteem
- 2019: ACM-W Inspire Conference Chair:
- 2019: Debate Panel member:
AI & Society: for better or for worse?
Panel of AI and social science experts to discuss the role of artificial intelligence in our society, organised by Durham University and NINE DT
- 2019: Invited Speaker : Unconventional Computation and Natural Computation Conference 2019, Tokyo, Japan
- 2019: Invited Speaker: A Celebration of the University’s Diverse Strengths in Research Symposium
- 2019: Invited Speaker @ Robert Gordon University, Aberdeen:
- 2019: Keynote Speaker at NGSchool: Summer School in Bioinformatics & NGS Data Analysis,
- 2019: Named among the top 30 women in AI in the UK by RE-WORK:
- 2019: Organiser of the Computational Neurosciences Special Session: at the 15th Conference on Computability in Europe (CiE 2019)
- 2019: Program Committee member:
International Workshop on Social & Emotion AI for Industry
- 2019: Roundtable Panel Member : Machine Learning and Digital Humanities. The event is supported by the Newcastle University Humanities Research Institute (NUHRI) and Animating Text Newcastle University (ATNU)
- 2018: BBC News coverage for the pilot study at Fellside Primary School: Discussing how the robotic head 'Robbie', will be used to help children with autism in the future.
- 2018: Invited Speaker: Technologies of Crime, Justice and Security Conference
- 2018: Invited Speaker and Panel Member: 3rd ACM-W UK Inspire Conference
- 2018: ITV news coverage for the pilot study at Fellside Primary School:
Discussing how the robotic head 'Robbie', will be used to help children with autism in the future.
- 2018: Sponsorship Chair: 29th British Machine Vision Conference
- 2018: Technical Program Committee Chair: ACM Multi Media Conference
- 2017: Area Chair: Women in Machine Learning Workshop (part of NIPS)
- 2017: Invited Speaker: Re-Work Deep Learning Summit - London
- 2016: Keynote Speaker: NVIDIA's GPU Programming and Machine Learning Workshop 'Deep Learning Applications powered by GPGPUs'
- Grants Reviewer for EPSRC :
- Grants Reviewer for the European Commission:
- Innovative Computing
- Natural Language Processing
- Machine Learning - Deep Learning
- Machine Learning for Healthcare
- Anomaly Detection
- Unsupervised Feature Learning
- Social Robotics
- Brain Computer Interfaces
- Evolutionary Computation
- Multi-Objective Optimisation
- Al Moubayed, N, Petrovski, A & McCall, J (2014). D2MOPSO: MOPSO Based on Decomposition and Dominance with Archiving Using Crowding Distance in Objective and Solution Spaces. Evolutionary Computation 22(1): 47-77.
Chapter in book
- Al Moubayed, N., Wall, D. & McGough, A. S. (2017). Identifying Changes in the Cybersecurity Threat Landscape using the LDA-Web Topic Modelling Data Search Engine. In Human aspects of information security, privacy and trust: 5th International Conference, HAS 2017, held as part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, proceedings. Tryfonas, Theo Cham: Springer. 287-295.
- Al Moubayed, N, Petrovski, A & McCall, J (2013). Mutual Information for Performance Assessment of Multi Objective Optimisers: Preliminary Results. In Intelligent Data Engineering and Automated Learning – IDEAL 2013. Springer Berlin Heidelberg. 8206: 537-544.
- Al Moubayed, N, Petrovski,A & McCall,J (2012). D 2 MOPSO: Multi-Objective Particle Swarm Optimizer Based on Decomposition and Dominance. In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg. 7245: 75-86.
- Al Moubayed, N, Petrovski, A & McCall, J (2011). Clustering-Based Leaders’ Selection in Multi-Objective Particle Swarm Optimisation. In Intelligent Data Engineering and Automated Learning - IDEAL 2011. Springer Berlin Heidelberg. 6936: 100.
- Al Moubayed, N, Petrovski, A & McCall, J (2010). A Novel Smart Multi-Objective Particle Swarm Optimisation using Decomposition. In Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg. 1-10.
- Alhassan, Zakhriya, Budgen, David, Alessa, Ali, Alshammari, Riyad, Daghstani, Tahini & Al Moubayed, Noura (2019), Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction, 28th International Conference on Artificial Neural Networks, ICANN2019. Munich, Germany, Springer.
- Aznan, N.K.N., Connolly, J.D., Al Moubayed, N. & Breckon, T.P. (2019), Using Variable Natural Environment Brain-Computer Interface Stimuli for Real-time Humanoid Robot Navigation, 2019 IEEE International Conference on Robotics and Automation (ICRA). Montreal, Canada, IEEE.
- Gajbhiye, Amit, Jaf, Sardar, Al-Moubayed, Noura, McGough, A. Stephen & Bradley, Steven (2018), An Exploration of Dropout with RNNs for Natural Language Inference, in Kurková, V., Manolopoulos, Yannis, Hammer, Barbara, Iliadis, Lazaros S. & Maglogiannis, Ilias G. eds, Lecture Notes in Computer Science, 11141 ICANN 2018: 27th International Conference on Artificial Neural Networks. Rhodes, Springer, Cham, 157-167.
- Gajbhiye, Amit, Jaf, Sardar, Al-Moubayed, Noura, Bradley, Steven & McGough, A. Stephen (2018), CAM: A Combined Attention Model for Natural Language Inference, in Abe, Naoki Liu, Huan Pu, Calton Hu, Xiaohua Ahmed, Nesreen Qiao, Mu Song, Yang Kossmann, Donald Liu, Bing Lee, Kisung Tang, Jiliang He, Jingrui & Saltz, Jeffrey eds, IEEE International Conference on BIG DATA. Seattle, United States of America, IEEE, Piscataway, N.J., 1009-1014.
- Vissol-Gaudin, E., Kotsialos, A., Groves, C., Pearson, C., Zeze, D.A., Petty, M.C. & Al-moubayed, N. (2018), Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers, 2018 IEEE World Congress on Computational Intelligence (WCCI 2018). Rio de Janeiro, Brazil, IEEE, Piscataway, 646-653.
- Aznan, N.K.N., Bonner, S., Connolly, J.D., Al Moubayed, N. & Breckon, T.P. (2018), On the Classification of SSVEP-Based Dry-EEG Signals via Convolutional Neural Networks, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018). Miyazaki, Japan, IEEE, Piscataway, NJ, 3726-3731.
- Alhassan, Z, Budgen, D, Alshammari, R, Daghstani, T, McGough, S & Al Moubayed, N (2018), Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data, 17th International Conference in Machine Learning and Applications (ICMLA2018). Orlando, Florida, USA, IEEE.
- Alhassan, Zakhriya, McGough, A. Stephen, Alshammari, Riyad, Daghstani, Tahani, Budgen, David & Al Moubayed, Noura (2018), Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data, IEEE 17th International Conference on Machine Learning and Applications (ICMLA 2018). Orlando, Fl, USA, IEEE, 541-546.
- Alhassan, Zakhriya, McGough, Stephen, Alshammari, Riyad, Daghstani, Tahini, Budgen, David & Al Moubayed, Noura (2018), Type-2 Diabetes Mellitus Diagnosis from Time Series Clinical Data using Deep Learning Models, in Kůrková, Věra, Manolopoulos, Yannis, Hammer, Barbara, Iliadis, Lazaros & Maglogiannis, Ilias eds, Lecture Notes in Computer Science 1141: International Conference on Artificial Neural Networks (ICANN). Rhodes, Greece, Springer, 468-478.
- McGough, S Forshaw, M, Brennan,J Al Moubayed, N & Bonner, S (2018), Using Machine Learning to reduce the energy wasted in Volunteer Computing Environments, 9th International Green and Sustainable Computing Conference. Pittsburgh, PA, US, IEEE, 1-8.
- Al Moubayed, Noura, Hasan, Bashar Awwad Shiekh & McGough, Andrew Stephen (2017), Enhanced detection of movement onset in EEG through deep oversampling, 30th International Joint Conference on Neural Networks (IJCNN 2017). Anchorage, Alaska, USA, IEEE, Piscataway, 71-78.
- A. S, McGough, N, Al Moubayed & M, Forshaw (2017), Using Machine Learning in Trace-driven Energy-Aware Simulations of High-Throughput Computing Systems, ICPE '17 Companion 3rd International Workshop on Energy-aware Simulation (ENERGY-SIM’17). L'Aquila, ACM, New York, 55-60.
- Al Moubayed, N., Breckon, T.P., Matthews, P.C. & McGough, A.S. (2016), SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder, in Villa, Alessandro E.P., Masulli, Paolo & Pons Rivero, Antonio J. eds, Lecture Notes in Computer Science 9887: Springer International Publishing, Cham, 423-430.
- Al Moubayed, N., Vazquez-Alvarez, Y., McKay, A. & Vinciarelli, A. (2014), Face-Based Automatic Personality Perception, MM '14 22nd ACM international conference on Multimedia - MM '14. Orlando, Florida, USA, Association for Computing Machinery (ACM), New York, NY, USA, 1153-1156.
- Al Moubayed, N , Awwad Shiekh Hasan, B Gan, J Q Petrovski, A & McCall, J (2012), Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces, 2012 IEEE Congress on Evolutionary Computation. Brisbane, Australia, IEEE, 1-7.
- Al Moubayed, N, Petrovski, A & McCall, J (2011), Clustering based leaders' selection in multi-objective evolutionary algorithms, Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11. Dublin, Irland, ACM.
- Al Moubayed, N, Petrovski, A & McCall, J (2011), Multi-objective Optimisation of Cancer Chemotherapy using Smart PSO with Decomposition, 2011 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making (MDCM). Paris, France, IEEE, 81 - 88.
- Al Moubayed, N , Awwad Shiekh Hasan, B, Gan, J Q Petrovski, A & McCall, J (2010), Binary-SDMOPSO and its application in channel selection for Brain-Computer Interfaces, 2010 UK Workshop on Computational Intelligence (UKCI). Colchester, UK, IEEE, 1-6.
- Windisch, A & Al Moubayed, N (2009), Signal Generation for Search-Based Testing of Continuous Systems, 2009 International Conference on Software Testing, Verification, and Validation Workshops. Denver, CO, IEEE.
- Al Moubayed, N & Windisch, A (2009), Temporal White-Box Testing Using Evolutionary Algorithms, 2009 International Conference on Software Testing, Verification, and Validation Workshops. Denver, CO, IEEE, 150.
- Al Moubayed, N & Awwad Shiekh Hasan, B (2009), Temporal White-Box Testing Using Evolutionary and Search-base Algorithms, 9th Annual Workshop on Computational Intelligence. Colchester, UK.
- Al Moubayed, N (Accepted). Multi-objective particle swarm optimisation: methods and applications. Robert Gordon University. PhD.
- 2019: Innovate UK with Cievert ltd, Machine Learning for Healthcare, (£227,547.00, 2.5 years)
- 2018: Creating ad campaign stories using synthetic visual cues (£18780.00 from )
- 2018: EPSRC CRITiCaL - Combatting cRiminals In The CLoud (Co-Investigator, Funding Value: £2,027,645)
- 2018: General Purpose Text Understanding using AI engine with Adaptive Sentiment Visualisation (£33780.00 from )
- 2018: Royal Society Partnership Grant with Fellside Primary School (Funding Value £5000)
- 2016: Phase 2: Open Source Big Data Insight. Automated Knowledge Discovery and Classification (Co-Investigator and Named Research Associate. Funding Value: £452,100.00)
- 2015: Phase 1: Open Source Big Data Insight. Automated Knowledge Discovery and Classification (Co-Investigator and Named Research Associate. Funding Value: £36,173.08)