Photo of Glenn Hawe
  • Shore Road, Jordanstown Campus

    BT37 0QB Newtownabbey

    United Kingdom

  • 253 Citations
  • 7 h-Index

Research output per year

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Personal profile


Glenn Hawe graduated from the University of Warwick in 2004 with a MPhys in Mathematics and Physics (first class), and from the University of Southampton in 2008 with a PhD in Electronics and Electrical Engineering. His PhD research concerned multi-objective Bayesian optimization algorithms for electromagnetic design, and was carried out whilst employed as a KTP Associate with Vector Fields, Oxford. During his PhD he won two best paper awards at conferences, and his work featured in the 2009 “From recession to recovery” report by Universities UK as an example of successful collaboration between academia and industry.

From 2008-2010 he was employed as a PDRA at the University of Manchester on the BBSRC-funded project "Novel force-fields devised through machine learning". Here he developed machine learning software (involving Gaussian Processes and Neural Networks) for use in a computational chemistry group optimizing regression algorithms for use in a force-field derived from quantum theory. From 2010-2013 he was employed as a PDRA at Durham University on the EPSRC-funded project "Adaptive Co-ordinated Emergency Response to Rapidly Evolving Large-Scale Unprecedented Events (REScUE)". Here he developed agent-based simulation and optimization software to explore computationally how to design responses to major incidents in the UK.

Glenn joined the School of Computing at the Ulster University as a lecturer in 2013. A member of the Artificial Intelligence Research Group, his current research focuses on machine learning and Bayesian optimization. He is a member of the EPSRC peer review college, and has acted as a reviewer for several journals and conferences in AI.

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Research Output

  • 253 Citations
  • 7 h-Index
  • 11 Article
  • 8 Conference contribution
  • 1 Chapter

Effect of Market Spread Over Reinforcement Learning Based Market Maker

Haider, A., Wang, H., Scotney, B. & Hawe, G., 3 Jan 2020, Machine Learning, Optimization, and Data Science - 5th International Conference, LOD 2019, Proceedings. Nicosia, G., Pardalos, P., Umeton, R., Giuffrida, G. & Sciacca, V. (eds.). Vol. 11943. p. 143-153 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11943 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Ontology-based Enriched Concept Graphs for Medical Document Classification

    Shanavas, N., Wang, H., Lin, Z. & Hawe, G., 2 Mar 2020, (Accepted/In press) In : Information Sciences.

    Research output: Contribution to journalArticle

  • Gated Task Interaction Framework for Multi-task Sequence Tagging

    Ampomah, I., McClean, S. I., Lin, Z. & Hawe, G., 7 Mar 2019, (Accepted/In press) 2019 International Joint Conference on Neural Networks, IJCNN 2019. IEEE, Vol. 2019-July. 8851801. (Proceedings of International Joint Conference on Neural Networks ).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Inspiration for Space 2.0 from Autonomic-ANTS Concept missions

    Sterritt, R., Wilkie, G., Saunders, C., Doran, M., Gama, C., Hawe, G. & McGuigan, L., 12 Nov 2019, Proceedings of the 17th BIS Reinventing Space Conference. British Interplanetary Society, BIS-RS-2019-39

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Towards a Cubesat Autonomicity Capability Model A Roadmap for Autonomicity in Cubesats

    Gama, C., Sterritt, R., Wilkie, G. & Hawe, G., 18 Feb 2018, Unknown Host Publication. International Academy, Research, and Industry Association, p. 34-43 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Open Access
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