Long Chen is a lecturer at the School of Computing, Mathematics, and Data Science at Coventry University. Prior to joining Coventry, he was a research fellow at the University of Glasgow. Long's research interests include cost-effective AI, digital health, and NLP. He has developed a strong international reputation for his research on cost-effective AI, particularly in the areas of cost and quality joint optimization. Long is among the pioneering researchers who have introduced novel mechanisms to optimize quality and cost in task allocation - a fundamental research issue. His research has resulted in several top conference and journal publications, including WWW, SIGIR, WSDM, CIKM, IEEE Transactions on Big Data, and Computer Journal, among others. The results have been extensively validated using real-world data, demonstrating superior performance.

Teaching Modules:

• 7143CEM - Programming for Data Science
• 7089CEM - Introduction to Statistical Methods for Data Science 
• 6057CEM - Artificial Neural Networks 

Research Insterest:

• AI for Healthcare Studies - Digital Epidemiology, Healthcare IoT
• NLP - Topic Modelling, Semantic Graph, Question Answering
• Cost-effective Machine Learning - Active Learning, Multi-task Learning, Contrastive Learning, Transfer Learning