Dr Julie Wall BSc MSc FHEA
Senior Lecturer in Computing
Intelligent Systems Research Group , Computing
Educational Affiliate Employee Member of the BCS
University of East London
London, E16 2RD
Since completing her PhD in Computing and Intelligent Systems, Dr Julie Wall worked as a researcher at Ulster University, developing spiking neural networks for sound localization applied to mobile robots. She joined the Multimedia and Vision (MMV) research group at Queen Mary, University of London as a senior researcher and technical lead in the REVERIE FP7 project (http://cordis.europa.eu/project/rcn/100323_en.html), which developed mixed reality spaces in real and virtual worlds. She managed the integration team across the project’s partners to produce the project prototypes. She then joined UEL as a Senior Lecturer in Computer Science & Informatics; and is now Program Leader of BSc (Hons) Computer Science and member of the Intelligent Systems Research Group. She is currently the academic supervisor of a KTP project. Her research involves machine learning, deep and convolutional neural networks, spiking neural networks, and augmented and virtual reality.
Badii, A., Glackin, C., Chollet, G., Dugan, N., Cannings, N., ,Wall, J., Tahir, S., Ghosh Ray, I., Rajarajan, M., Falkner. R. "A Roadmap for Privacy Preserving Speech Processing" EAB Workshop on Preserving Privacy in an Age of Increased Surveillance – A Biometrics Perspective, pp 1-13, 2016.
Wall, J., Glackin, C., Cannings, N., Chollet, G., Dugan, N., “Recurrent lateral inhibitory spiking networks for speech enhancement,” IEEE International Joint Conference on Neural Networks (IJCNN), 2016.
Doumanis, I., Wall, J. and Monaghan, D., “Playing immersive games on the REVERIE platform”, Workshop on Virtual Environments and Advanced Interfaces (VEAI), October 2015.
M Pasin, A Frisiello, J Wall, S Poulakos, A Smolic, “A Methodological Approach to User Evaluation and Assessment of a Virtual Environment Hangout”, 7th International Conference on Intelligent Technologies for Interactive Entertainment (INTETAIN), June 2015.
Wall, J., Izquierdo, E., Argyriou, L., Monaghan, D., O’Connor, N., Poulakos, S., Smolic, A. & Mekuria, R., “REVERIE: Natural Human Interaction in Virtual Immersive Environments”, 21st IEEE International Conference on Image Processing (ICIP), pp. 2022-2024, 2014.
Wall, J. and Glackin, C., EBook: “Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding”, Frontiers Media SA., ISBN: 978-2-88919-239-7, 2014.
O’Connor, N.E., Alexiadis, D., Apostolakis, K., Daras, P., Izquierdo, E., Li, Y., Monaghan, D.S., Rivera, F., Stevens, C., Van Broeck, S., Wall, J. & Wei, H., “Tools for User Interaction in Immersive Environments”, MultiMedia Modeling, pp. 382-385, Springer International Publishing, 2014.
Wall, J. and Glackin, C., “Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding”, Frontiers in Computational Neuroscience, vol. 7, no. 182, 2013.
Mauro, D.A., Poulakos, S., O’ Connor, N.E., Monaghan, D., Gowing, M., Fechteler, P., Wall, J. & Izquierdo, E., “Advancements and Challenges towards a Collaborative Framework for 3D Tele-Immersive Social Networking”, 4th IEEE International Workshop on Hot Topics in 3D (Hot3D), 2013.
Kuijk, F., Dareau, C., Ravenet, B., Ochs, M., Apostolakis, K., Daras, P., Monaghan, D., O'Connor, N., Wall, J., Izquierdo, E. & Van Broeck, S., “A Framework for Human-like Behavior in an Immersive Virtual World”, 18th International Conference on Digital Signal Processing, DSP, 2013.
Wall, J. and Izquierdo, E., “Fuzzy Ensembles for Embedding Adaptive Behaviours in Semi-Autonomous Avatars in 3D Virtual Worlds”, 18th International Conference on Digital Signal Processing, DSP, 2013.
Fechteler, P., Eisert, P., Hilsmann, A., Mauro, D., Broeck, S., Kuijk, F., Monaghan, D., Cesar, P., Daras, P., Wall, J., Zahariadis, T., Mekuria, R., Sanna, M., Alexiadis, D. & Stevens, C., “A Framework for Realistic 3D Tele-Immersion”, International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications (Mirage), 2013.
Wall, J. A., McDaid, L. J., Maguire, L. P. & McGinnity, T.M. "Spiking neural network model of sound localisation using the interaural intensity difference", IEEE Transactions on Neural Networks, vol. 23, no. 4, pp. 574—586, 2012.
Wall, J. A., McGinnity, T. M. & Maguire, L. P., “Using the interaural time difference and cross-correlation to localise short-term complex noises,” The 22nd Irish Conference on Artificial Intelligence and Cognitive Science (AICS), pp. 375, 2011.
Wall, J. A., McGinnity, T. M. & Maguire, L. P., “A comparison of sound localisation techniques using cross-correlation and spiking neural networks for mobile robotics,” IEEE International Joint Conference on Neural Networks (IJCNN), 2011.
Glackin, B., Wall, J. A., McGinnity, T.M., Maguire, L. P. & McDaid, L. J. "A Spiking Neural Network Model of the Medial Superior Olive using Spike Timing Dependent Plasticity for Sound Localisation", Frontiers in Computational Neuroscience, vol. 4, pp. 1-16, 2010.
Wall, J. A., McDaid, L. J., Maguire, L. P. & McGinnity, T.M. "Spiking neuron models of the medial and lateral superior olive for sound localisation", IEEE International Joint Conference on Neural Networks (IJCNN) (IEEE World Congress on Computational Intelligence), pp. 2641-2647, 2008.
Wall, J. A., McDaid, L. J., Maguire, L. P. & McGinnity, T. M. "A spiking neural network implementation of sound localisation", Proc. of the IET Irish Signals and Systems, pp. 19-23, 2007
Wall, J. “Perception-based Modelling of System Behaviour,” Proc. of the IEEE Systems, Man and Cybernetics Society, pp. 312-317, 2006.
‘International Women’s Day 2016: Women in tech have their say’, Tech City News, March 2016, http://techcitynews.com/2016/03/08/international-womens-day-2016-women-in-tech-have-their-say/
‘The rise of the machines: How AI can transform our lives’, Tech City News, July 2016, http://techcitynews.com/2016/07/21/rise-machines-ai-can-transform-lives/
Wall, J., Glackin, C., ‘Speech enhancement with recurrent lateral inhibitory spiking networks’, UEL Research Conference, 2016
Wall, J., Poster: "Deep Laterally Recurrent Spiking Neural Networks for Speech Enhancement", UEL Computing & Engineering Showcase, June 2016
CN5121 Data Structures and Algorithms
CN4101 Information Systems Modelling and Design
CN5101 Database Systems