Xiancheng Li

Xiancheng Li is a post-doctoral researcher at Queen Mary University of London's School of Business and Management, working with Professor Pietro Panzarasa and Dr. Anna de Simoni in the AD HOC program. This initiative develops online communities to help people with troublesome asthma manage their condition through social interactions. Previously, he completed his PhD at the Centre for Globalisation Research within the same institution, investigating academic collaborations and innovation through computational methods.

His research centers on analyzing network patterns in online health communities and evaluating correlations between network structures and health outcomes. He applies natural language processing to track thematic evolution in user discussions, bridging health informatics, social network analysis, and machine learning. Key methodologies include deep learning for sentiment analysis and computational modeling of user engagement dynamics in respiratory disease communities.

His publication record shows a dual research trajectory: health informatics applications in asthma and Parkinson's disease management, and methodological advances in network analysis for academic collaboration studies. Recent work demonstrates expertise in deep learning-based community analysis and the 'academic Great Gatsby curve' concept, consistently employing computational social science approaches across both domains.

No scientific awards were documented in the source material.

Li has served as Teaching Associate for Machine Learning and Digital Technology (2023-2025) and Social Network Analysis (2020). The available information does not reference research grants he has secured or students he has formally advised.

He is an active member of the AD HOC program team, which develops digital interventions connecting asthma patients through structured online communities. This interdisciplinary project integrates computer science, health research, and clinical practice to create evidence-based social support systems for chronic disease management.