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Northumbria’s global footprint touches every continent across the world, through our global partnerships across 17 institutions in 10 countries, to our 277,000 strong alumni community and 150 recruitment partners – we prepare our students for the challenges of tomorrow. Discover more about how to join Northumbria’s global family or our partnerships.
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The world is changing faster than ever before. The future is there to be won by organisations who find ways to turn today's possibilities into tomorrows competitive edge. In a connected world, collaboration can be the key to success.
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Northumbria University is renowned for the calibre of its business-ready graduates. Our alumni network has over 253,000 graduates based in 178 countries worldwide in a range of sectors, our alumni are making a real impact on the world.
Our Alumni - Work For Us
Dr. Yulei Li, a lecturer in Computer and Information Sciences at Northumbria University, specialises in applying AI and machine learning to business challenges. He has co-led two KTP projects using AI to solve business problems. His expertise spans machine learning model development, autonomous agents, large language models and predictive systems.
Dr. Yulei Li’s research interests centre around the development and application of Large Language Models (LLMs), machine learning, and big data analytics, with a strong focus on business contexts. He also applies LLMs and AI technologies to real-world industrial challenges through Knowledge Transfer Partnerships, contributing to innovation in organisational wellbeing, obsolescence management, and strategic business processes.
- Please visit the Pure Research Information Portal for further information
- Leveraging AI to capture textual and visual elements: Insights for HRM research and practice, Liang, Y., Aroles, J., Li, Y. 11 Feb 2026, In: Human Resource Management Journal
- Using large-language models to analyse social media engagement with the public sector communication on circular economy: Evidence from X, Li, Y., Cao, D., Hewitt, M., Shan, S. 1 Jan 2026, In: Technological Forecasting and Social Change
- Augmenting Orbital Debris Identification with Neo4j-Enabled Graph-Based Retrieval-Augmented Generation for Multimodal Large Language Models, Roll, D., Kurt, Z., Li, Y., Woo, W. 26 May 2025, In: Sensors
- Frigate: A Novel Dataset Comprising Wide Field of View Astronomical FITS Images of Low Earth Orbit Scenes for Machine Learning Applications, Roll, D., Kurt, Z., Li, Y., Dinsley, R., Woo, W. 19 Dec 2025, In: Scientific data
- Detect2Interact: Localizing Object Key Field in Visual Question Answering (VQA) with LLMs, Wang, J., Zhu, M., Li, Y., Li, H., Yang, L., Woo, W. 1 May 2024, In: IEEE Intelligent Systems
- Text Mining and Topic Modelling, Li, Y., Shan, S., Lin, Z. 14 Dec 2023, Researching and Analysing Business, London, Routledge
- Customer Emotions in Service Robot Experiences: A Hybrid Machine-Human Intelligence Approach, Filieri, R., Lin, Z., Li, Y., Lu, X., Yang, X. 1 Nov 2022, In: Journal of Service Research
- Using social media big data for tourist demand forecasting: A new machine learning analytical approach, Li, Y., Lin, Z., Xiao, S. 2022, In: Journal of Digital Economy
- National Culture and Culinary Exploration: Japan Evidence of Heterogenous, Liu, B., Wang, Y., Katsumata, S., Li, Y., Gao, W., Li, X. 25 Nov 2021, In: Frontiers in Psychology - Organisational Psychology
- A Warning System for the Return of COVID-19 by Using the Social Media Data, Shan, S., Li, Y. 2020, IEEE International Conference on Data Analytics for Business and Industry
Our Staff
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- Dongjun Li
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