|Alma mater||University of Leeds|
|Fields||Computer Science, Cognitive Science|
Hannah Dee is a British cognitive scientist and computer scientist specialising in computer vision, with specialisms in plant science, navigation, art, and medical imaging. In 2014, she was one of 30 women identified by the British Computer Society in the "BCS Women in IT Campaign.
Dee has organised many events for women in computing and for broader groups with a women-friendly stance, including an android programming family fun day (materials available in Welsh and in English).
Dee received a BSc in Cognitive Science (1996), an MA in Philosophy (1998), and a PhD in Computing (2005), all from the University of Leeds, and she has held post-docs at Kingston University (2005-2006), University of Leeds (2006-2009), and Institut National Polytechnique de Grenoble (2009-2010). Since 2010, she is a Senior Lecturer in computer science at Aberystwyth University.
She has been deputy chair of her local BCS branch (BCS Mid Wales) since 2011.
Dee developed and runs the annual BCSWomen Lovelace Colloquium, the one-day conference for women computing students to encourage networking for women students from around the UK, in addition to gaining career development advice from successful women in computing.
Her research areas in computer vision for the analysis of human behaviour; shadow detection and reasoning; and student attitudes to the study of computer science. She is noted for championing the cause of women in IT.
Awards and Recognitions
In 2014 Dee was featured in the e-book of these 30 women in IT, "Women in IT: Inspiring the next generation” produced by the BCS, The Chartered Institute for IT, as a free download e-book, from various sources. In 2016, Dee was identified as one of the 50 most influential women in UK IT 2016 by Computer Weekly.
In 2015, Dee was identified as the 10th Most Influential Women in UK IT 2015, by Computer Weekly.
Roscoe, Dee, Zwiggelaar, Coping with Noise in Ultrasound Images: A review, MIUA 2012 
Ngoc-Son Vu, Hannah M. Dee and Alice Caplier "Face Recognition using the POEM descriptor", Pattern Recognition
Hannah M. Dee, Cohn, A. G. and Hogg, D. C. "Building semantic scene models from unconstrained video" Volume 116, Issue 3, March 2012, Pages 446.456 
Paul Robson, Michal Mos, Hannah Dee, John Clifton-Brown and Iain Donnison (2011). Improving bioenergy crop yield and quality through manipulating senescence. In: Biomass and Bioenergy Crops IV. Aspects of Applied Biology 112, pp. 323–328.
Hannah M. Dee & Paulo E. Santos (2011): The Perception and Content of Cast Shadows: An Interdisciplinary Review, Spatial Cognition & Computation, 11:3, 226–25.
Dee, H. M. and Caplier, A. "Crowd behaviour analysis using histograms of motion direction", IEEE International Conference on Image Processing (ICIP), 2010, Hong Kong.
Santos, P. E., Dee, H. M. and Fenelon, V. "Knowledge-based adaptative thresholding from shadows" Accepted at the European Conference on Artificial Intelligence (ECAI), 2010, Lisbon, Portugal.
- "Research - Hannah Dee's home page". users.aber.ac.uk. Retrieved 2018-07-25.
- "Women in IT". BCS. Retrieved 14 October 2014.
- "Android Programming Fun Day".
- "Staff Profiles". Aberystwyth University. Retrieved 4 October 2013.
- Women in IT: Inspiring the next generation (PDF). British Computer Society. 1 October 2014. p. 57. ISBN 978-1-78017-287-3. Retrieved 14 October 2014.
- Computer Weekly http://www.computerweekly.com/news/450295511/Vote-for-the-most-influential-woman-in-UK-IT-2016. Retrieved 30 May 2016. Missing or empty
- "Computer Weekly Most Influential Women UK IT 2014". Retrieved 1 July 2014.
- Bateman, Kayleigh (2015-07-06). "The 50 most influential women in UK IT 2015: 10. Dr Hannah Dee, Lecturer in Computer Science at Aberystwyth University". Computer Weekly. Retrieved 11 July 2015.
- "Most Influential Women in UK IT 2018: Entrants to the Hall of Fame". Computer Weekly. Computer Weekly. Retrieved 22 January 2019.
- "Coping with Noise in Ultrasound Images: A review".
- "Face Recognition using the POEM descriptor".
- "Building semantic scene models from unconstrained video".
- "Improving bioenergy crop yield and quality through manipulating senescence".
- "The Perception and Content of Cast Shadows: An Interdisciplinary Review, Spatial Cognition & Computation".
- "Crowd behaviour analysis using histograms of motion direction".
- "Knowledge-based adaptative thresholding from shadows".