Dr Jay Morgan

Tiwtor, Computer Science

j.p.morgan@abertawe.ac.uk

Siaradwr Cymraeg Sylfaenol

015
Llawr Gwaelod
Y Ffowndri Gyfrifiadol
Campws y Bae

Dolenni Ymchwil

https://orcid.org/0000-0003-3719-362X

ResearchGate

Google Scholar

Scopus

Trosolwg

Derbyniodd Dr Jay Paul Morgan ei PhD o'r Adran Gyfrifiadureg, Prifysgol Abertawe. Mae'r gwaith hwn yn datblygu dulliau ynghylch sut i gyfuno gwybodaeth arbenigol â rhwydweithiau niwral dwys mewn llawer o feysydd gwyddonol. Mae Jay, drwy ei PhD, wedi gweithio ym meysydd arbenigol cemeg cwantwm, ieithyddiaeth ac astroffiseg.

Yn nes ymlaen, daliodd Jay swydd ôl-ddoethurol ym Mhrifysgol Toulon, Ffrainc, fel rhan o Labordy CNRS-LIS. Ymchwiliodd y gwaith hwn, mewn cydweithrediad ag Arsyllfa Paris-Meudon, i sut gall technegau prosesu rhagarweiniol wella delweddu ein haul. Mae Jay bellach yn Diwtor mewn Cyfrifiadureg ym Mhrifysgol Abertawe, lle mae'n rhan o'r grŵp ymchwil Cyfrifiadureg Ddamcaniaethol.

Mae Jay hefyd yn rhan o STRONG (tîm Abertawe sy'n ymchwilio i feithrin perthnasoedd amhriodol ar-lein) a SING (Swansea Icons Norm Group) a gynhelir yn yr Adran Seicoleg.

Gwefan bersonol

Meysydd Arbenigedd

Dysgu Dwfn
Prosesu Iaith Naturiol

Uchafbwyntiau Gyrfa

Diddordebau Addysgu

Ystadegau

Dysgu Peirianyddol

Ieithoedd rhaglennu

Cyhoeddiadau

Uchafbwyntiau Ymchwil

Morgan, J., Morgan, J., Paiement, A., Williams, J., Wyner, A., & Seisenberger, M. (2018). A Chatbot Framework for the Children’s Legal Centre. In Frontiers in Artificial Intelligence and Applications (pp. 205-209).
https://doi.org/10.3233/978-1-61499-935-5-205, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48384
http://ebooks.iospress.nl/volumearticle/50853
Morgan, J. & MORGAN, J. (2022). Strategies to use Prior Knowledge to Improve the Performance of Deep Learning (Subtitle) An Approach Towards Trustable Machine Learning Systems
https://doi.org/10.23889/SUthesis.59258, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59258
Morgan, J., Paiement, A., & Klinke, C. (2023). Domain-informed graph neural networks: A quantum chemistry case study. Neural Networks, 165, 938-952.
https://doi.org/10.1016/j.neunet.2023.06.030, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63771
http://dx.doi.org/10.1016/j.neunet.2023.06.030
Morgan, J., Crook, T., Morgan, J., Pauly, A., & Roggenbach, M. (2023). A Computability Perspective on (Verified) Machine Learning. In Recent Trends in Algebraic Development Techniques (pp. 63-80). Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-43345-0_3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63849

Holl Ymchwil

Erthyglau Cylchgronau

Morgan, J., Paiement, A., & Klinke, C. (2023). Domain-informed graph neural networks: A quantum chemistry case study. Neural Networks, 165, 938-952.
https://doi.org/10.1016/j.neunet.2023.06.030, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63771
http://dx.doi.org/10.1016/j.neunet.2023.06.030

Cyfraniadau Cynadleddau

Morgan, J., Crook, T., Morgan, J., Pauly, A., & Roggenbach, M. (2023). A Computability Perspective on (Verified) Machine Learning. In Recent Trends in Algebraic Development Techniques (pp. 63-80). Springer Nature Switzerland.
https://doi.org/10.1007/978-3-031-43345-0_3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63849
Morgan, J., Morgan, J., Paiement, A., Williams, J., Wyner, A., & Seisenberger, M. (2018). A Chatbot Framework for the Children’s Legal Centre. In Frontiers in Artificial Intelligence and Applications (pp. 205-209).
https://doi.org/10.3233/978-1-61499-935-5-205, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48384
http://ebooks.iospress.nl/volumearticle/50853

Cynnyrch Ymchwil Arall

Morgan, J. & MORGAN, J. (2022). Strategies to use Prior Knowledge to Improve the Performance of Deep Learning (Subtitle) An Approach Towards Trustable Machine Learning Systems
https://doi.org/10.23889/SUthesis.59258, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa59258