Dr Hannah Dee

BSc, MA, PhD University of Leeds

Dr Hannah Dee

Senior Lecturer

Department of Computer Science

Contact Details

Profile

Hannah has a BSc in Cognitive Science (1996), an MA in Philosophy (1998) and a PhD in Computing (2005) all from the University of Leeds. Her research areas are applied computer vision; the detection of shadows and reasoning about shadows; and student attitudes to the study of computer science. She has held postdoctoral positions in Grenoble (France), Leeds, and Kingston upon Thames. She is also a women in computing activist: she founded the BCSWomen Lovelace Colloquium, a national conference for women undergraduates in computer science, and is still deputy chair. She has been on the committee of BCSWomen since 2007.

Teaching

Module Coordinator
Moderator
Coordinator
Lecturer
Additional Lecturer
Tutor

Hannah enjoys teaching and has received several teaching awards since arriving in Aberystwyth:

  • Senior fellowship of the HEA (SFHEA), 2018
  • Student led teaching awards (SLTA), highly commended, technology enhanced learning category, 2016
  • Exemplary Course Awards (ECA), highly commended for Computer Vision, 2015
  • Exemplary Course Awards (ECA), highly commended for Client Side Graphics module, 2014
  • Student led teaching awards (SLTA), highly commended, teaching through technology category, 2013
  • Aberystwyth University Learning and Teaching Fellowship (AULTF), 2012

Research Groups

Publications

Seck, A, Dee, H, Smith, W & Tiddeman, B 2019, '3D surface texture analysis of high‐resolution normal fields for facial skin condition assessment' Skin Research and Technology. https://doi.org/10.1111/srt.12793
Bell, J & Dee, H 2019 'Leaf segmentation through the classification of edges' arXiv. https://doi.org/arXiv:1904.03124
Newey, C, Jones, O & Dee, H 2017, 'Shadow detection for mobile robots: Features, evaluation, and datasets' Spatial Cognition and Computation, pp. 1-23. https://doi.org/10.1080/13875868.2017.1322088
Bell, J & Dee, H 2017, 'Watching plants grow: A position paper on computer vision and Arabidopsis thaliana' IET Computer Vision, vol. 11, no. 2, pp. 113-121. https://doi.org/10.1049/iet-cvi.2016.0127
Santos, PE, Martins, MF, Fenelon, V, Cozman, FG & Dee, H 2016, 'Probabilistic self-localisation on a qualitative map based on occlusions' Journal of Experimental & Theoretical Artificial Intelligence, vol. 28, no. 5, pp. 781-799. https://doi.org/10.1080/0952813X.2015.1132265
More publications on the Research Portal