Dr Julie Wall
Reader in Computer Science, Director of Impact and Innovation
NLP/NLU, Explainable AI, Deep Learning, Spiking Neural Networks, Virtual/Augmented/Mixed Reality
Department of Computer Science and Digital Technologies , 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.
- PhD, MSc, BSc, FHEA
- Fellow of the Higher Education Academy
- Professional Member of the British Computer Society (995114789)
- IEEE Member (93605062)
- Associate Member Cambridge Wireless
Areas Of Interest
- Natural Language Processing
- Machine learning
- Deep learning
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.
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
- Roman Shrestha, Cornelius Glackin, Julie Wall, Nigel Cannings, Marvin Rajwadi, Satya Kada, James Laird, Thea Laird and Chris Woodruff, Speaker Recognition using Multiple X-Vector Speaker Representations with Two-Stage Clustering and Outlier Detection Refinement, 7th IEEE Cyber Science and Technology Congress (CyberSciTech), 2022.
- Nossier, S A., Wall, J., Moniri, M., Glackin, C., Cannings, Convolutional Recurrent Smart Speech Enhancement Architecture for Hearing Aids, INTERSPEECH 2022.
- Nossier, S A., Wall, J., Moniri, M., Glackin, C., Cannings, A two-stage DNN for speech enhancement and reconstruction in the frequency and time domains, IEEE International Joint Conference on Neural Networks (IJCNN), 2022.
- Poobalasingam, V., Cannings, N., Glackin, C., Wall, J., Sharif S., Moniri, M., A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings, 7th International XR Conference, 2022.
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
- 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.Read more
BSc (Hons) Data Science and Artificial Intelligence
The Data Science and Artificial Intelligence combines two key areas of computing: data science and artificial intelligence.Read more
- 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
- External Examiner, University of Chester
- Intelligent Voice Ltd.