Dr Yulei Li

Lecturer

Department: Computer and Information Sciences

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.

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Research Themes and Scholarly Interests

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.

Key Publications

Please visit the Pure Research Information Portal for further information
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
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
What E-gov System should African Countries Invest? A Panel Data Analysis, Li, Y., Shan, S., Lin, Z. 2020, UK Academy for Information System Conference Proceedings
A sentiment analysis of peer to peer energy trading topics from Twitter, Shan, S., Li, H., Li, Y. 31 Dec 2019, In: Proceedings of the International Conference on Electronic Business (ICEB)
Attracting Chinese FDI in Africa: The role of natural resources, market size and institutional quality, Shan, S., Lin, Z., Li, Y., Zeng, Y. 8 May 2018, In: Critical Perspectives on International Business