I am the interim Head of School for Computing, Mathematics and Digital Technology. My substantive post is the Head of Division: Computer Science and Information Systems. I have a research background in Artificial Intelligence with a PhD in Artificial Neural Networks. My teaching interests centre on Software Development and I have recently taught courses in Data Structures and Algorithms, Comparative Programming languages and applied courses such as Website Development and Mobile Application Development. In recent years I have concentrated on creating collaborations and knowledge exchange between universities and industry with a focus on the SME sector. I have led several large projects funded by Innovate UK, the Digital R&D Fund for the Arts, and the European Research Council. I am on the organising committee for the Manchester Raspberry Pi Jam and sit on the BCS Manchester branch committee.
D. Dancey, ZA. Bandar, D. McLean (2007). Logistic model tree extraction from artificial neural networks. IEEE Trans Syst Man Cybern B Cybern. 37(4), pp.794-802.
S. Khalid, S. Ul Hassan, M. Shardlow, D. Dancey, R. Nawaz Author Name Disambiguation on Ambiguous Data of Chinese Authors using Machine Learning Approaches. 26/9/2019.
J. Alarifi, J. Fry, D. Dancey, MH. Yap (2019). Understanding Face Age Estimation: humans and machine. In: 2019 International Conference on Computer, Information and Telecommunication Systems (CITS). 28/8/2019.
M. Kayani, S-U. Hassan, NR. Aljohani, D. Dancey, L. Liu, et al. (2019). Towards Interdisciplinary Research: A Bibliometric View of Information Communication Technology for Development in Different Disciplines. In: 2019 Third World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4). London, UK, 30/7/2019. pp.185-192.
D. Wilson, R. Nawaz, O. Kayas, D. Dancey, K. Welch 'The web is not print’: tracing historical influences on changing web coding practices. Amsterdam, 19/6/2019.
JS. Alarifi, M. Goyal, AK. Davison, D. Dancey, R. Khan, et al. (2017). Facial Skin Classification Using Convolutional Neural Networks. In: IMAGE ANALYSIS AND RECOGNITION, ICIAR 2017. Montreal, CANADA, 5/7/2017. pp.479-485.