Julie Wall

Dr Julie Wall

Reader

Intelligent systems, processing and modelling temporal data

Department of Engineering & Computing , School of Architecture, Computing and Engineering (ACE)

Julie joined UEL in 2015 as a Senior Lecturer and later became Reader in Computer Science and the Director of Impact and Innovation for the School of Architecture, Computing and Engineering. She is currently the course leader for BSc (Hons) Data Science and Artificial Intelligence. Her research focuses on deep neural networks for natural language processing/understanding and she maintains collaborative R&D links with the industry.

Qualifications

  • PhD, MSc, BSc, FHEA

Areas Of Interest

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  • Artificial intelligence
  • Machine learning
  • Deep learning
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On This Page

OVERVIEW

Dr Julie Wall leads the Intelligent Systems Group and is the Director of Impact and Innovation for the School of Architecture, Computing and Engineering. Her research interests focus on machine and deep learning approaches to natural language processing, natural language understanding and speech enhancement. She maintains collaborative research and development links with industry, through successful funding from Innovate UK.

CURRENT RESEARCH

The key theme of my research to date has been the design of intelligent systems for processing and modelling temporal data. I have explored neural network architectures, in terms of biologically inspired modelling and computationally efficient machine learning, on a variety of data structures from numerical, audio, images, video, to three-dimensional feature data from virtual and augmented reality environments. From my independent research career to date, my most significant scientific contributions concern: 

  • Deep learning architectures, algorithms and applications for audio, speech and natural language understanding
  • Application of intelligent systems to immersive virtual, augmented and mixed environments
  • Development of biologically inspired deep learning for speech recognition and enhancement
  • Privacy preserving intelligent systems for audio processing

Most recent research

  • Shrestha, R., Glackin, C., Wall, J. and Cannings, N., 2021, September. Bird Audio Diarization with Faster R-CNN. In International Conference on Artificial Neural Networks (pp. 415-426). Springer, Cham.
  • Goodluck Constance, T., Bajaj, N., Rajwadi, M., Maltby, H., Wall, J., Moniri, M., Woodruff, C., Laird, T., Laird, J., Glackin, C. and Cannings, N., 2021, September. Resolving Ambiguity in Hedge Detection by Automatic Generation of Linguistic Rules. In International Conference on Artificial Neural Networks (pp. 369-380). Springer, Cham.
  • Nossier, S.A., Wall, J., Moniri, M., Glackin, C. and Cannings, N., 2021. An Experimental Analysis of Deep Learning Architectures for Supervised Speech Enhancement. Electronics, 10(1), p.17.
  • Nossier, S.A., Wall, J., Moniri, M., Glackin, C. and Cannings, N., 2020, July. A Comparative Study of Time and Frequency Domain Approaches to Deep Learning based Speech Enhancement. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
  • Nossier, S.A., Wall, J., Moniri, M., Glackin, C. and Cannings, N., 2020, July. Mapping and Masking Targets Comparison using Different Deep Learning based Speech Enhancement Architectures. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.
  • Intelligent Systems Research Group

PUBLICATIONS

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  • Glackin, C., Wall, J., Chollet, G., Dugan N. and Cannings, N., "TIMIT and NTIMIT Phone Recognition using Convolutional Neural Networks", Pattern Recognition Applications and Methods (ICPRAM 2018), Lecture Notes in Computer Science (LNCS), vol 11351, Springer, 2018.
  • C. Glackin, J. Wall, G. Chollet, N. Dugan, N. Cannings, "Convolutional Neural Networks for Phoneme Recognition", 7th International Conference on Pattern Recognition Applications and Methods, 2018
  • C. Glackin, G. Chollet, N. Dugan, N. Cannings, J. Wall, S. Tahir, I. Ghosh Ray, M. Rajarajan, "Privacy preserving encrypted phonetic search of speech data", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
  • D. Schatz, R. Bashroush, J. Wall, "Towards a More Representative Definition of Cyber Security", Journal of Digital Forensics, Security and Law, 2017
  • Badii, C. Glackin, G. Chollet, N. Dugan, N. Cannings, J. Wall, S. Tahir, I. Ghosh Ray, M. Rajarajan, R. Falkner, "A Roadmap for Privacy Preserving Speech Processing", EAB Workshop on Preserving Privacy in an Age of Increased Surveillance - A Biometrics Perspective, 2017
  • M. Reljan-Delaney, J. Wall, "Solving the linearly inseparable XOR problem with spiking neural networks", SAI Computing Conference, 2017
  • 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), 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), 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.
  • 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.
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FUNDING

Total funding: £2,277,177

  • Apr 2019 - Mar 2021 - Innovate UK, "Automation and Transparency across Financial and Legal services: Mitigating Risk, Enhancing Efficiency and Promoting Customer Retention through the Application of Voice and Emotional AI", £2,005,177 (total), £473,479 (UEL)
  • Sept 2018 - Aug 2021 - Knowledge Transfer Partnership (KTP), Innovate UK, "Improving Video Conferencing with Augmented Reality", £268,000
  • Mar 2018 - May 2018 - UEL Funded Internship Scheme, "Development of computing taster sessions to support outreach & recruitment", £2,000
  • June 2018 - Oct 2018 - UEL Funded Research Internship, "Deep Learning for Speech Enhancement in Noisy Environments", £2000

TEACHING

  • Final year project supervision
  • MSc dissertation supervision
  • PhD Supervision: 2019-2022, Soha Abdallah, Industrial PhD studentship
  • Completed PhDs: 2014-2019, Dr Daniel Schatz

BSc (Hons) Computer Science

Learn all about computer science: software engineering, AI, information security and data analytics, computer systems, databases and networks.

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BSc (Hons) Data Science and Artificial Intelligence

The Data Science and Artificial Intelligence combines two key areas of computing: data science and artificial intelligence.

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Modules

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  • CN7023 Artificial Intelligence and Machine Vision
  • CN6121 Artificial Intelligence
  • CN5009 Mental Wealth: Professional Life 2 (Computing in Practice)
  • CN6123 Work Based Learning
  • CN3104 Applied Mathematics
  • CN5121 Data Structures and Algorithms
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EXTERNAL ROLES

  • External Examiner, University of Chester

INDUSTRY PARTNERS

  • Intelligent Voice Ltd.
  • Strenuus Ltd.
  • Lexiqal Ltd.