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Dr. Bing Wang

Lecturer in Data Analytics

Specialisms

  • Optimization Theory, 
  • Machine Learning, 
  • Data Analytics, 
  • Digital Health

Location

Whiteknights Campus

Bing Wang specialises in Machine Learning and Optimization Theory, with research interests spanning Natural Language Processing, Topological, Geometric and Multimodal Machine Learning for intelligent and trustworthy healthcare solutions.

Bing Wang has also been working as a Data Scientist at Royal Berkshire Hospital since December 2019 and at Oxford University Hospitals since February 2024. His work bridges academic research and real-world healthcare applications, focusing on the development and application of AI-driven approaches to clinical and public health challenges. His research interests include clinical decision support, intelligent healthcare systems, and the responsible adoption of AI, with a particular emphasis on developing data-driven solutions that are transparent, equitable, and trustworthy. Beyond healthcare, he is interested in interdisciplinary applications of machine learning in areas including finance, economics, management, climate change, and air pollution.

Reference: Wang, B. , Li, W. , Bradlow, A., Watt, A., Chan, A. T. Y. and Bazuaye, E. (2025) Multi-stage multimodal fusion network with language models and uncertainty evaluation for early risk stratification in rheumatic and musculoskeletal diseases. Information Fusion, 120. 103068. ISSN 15662535 doi: 10.1016/j.inffus.2025.103068
Henley faculty authors:
Dr. Bing Wang - Professor Weizi (Vicky) Li
Reference: Moon, P. , Li, W. , Chan, A., Wang, B. and Bazuaye, E. (2025) Explainable machine learning-based prediction of psoriatic arthritis flares using heterogenous real-world data for personalised patient care. Methods. ISSN 1046-2023 doi: 10.1016/j.ymeth.2025.10.010 (In Press)
Henley faculty authors:
Professor Weizi (Vicky) Li - Dr. Bing Wang
Reference: Wang, B. , Li, W. , Bradlow, A., Chan, A. T. Y. and Bazuaye, E. (2024) Early detection of inflammatory arthritis to improve referrals using multimodal machine learning from blood testing, semi-structured and unstructured patient records. In: The 57th Hawaii International Conference on System Sciences, 3-6 Jan 2024, Hawaii, pp. 3416-3424.
Henley faculty authors:
Dr. Bing Wang - Professor Weizi (Vicky) Li
Reference: Li, X., Huang, D., Dong, G. and Wang, B. (2024) Why consumers have impulsive purchase behavior in live streaming: the role of the streamer. BMC psychology, 12 (1). 129. ISSN 2050-7283 doi: 10.1186/s40359-024-01632-w
Henley faculty authors:
Dr. Bing Wang
Reference: Wang, B. , Li, W. , Bradlow, A., Bazuaye, E. and Chan, A. T. Y. (2023) Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning. Decision Support Systems, 166. 113899. ISSN 0167-9236 doi: 10.1016/j.dss.2022.113899
Henley faculty authors:
Dr. Bing Wang - Professor Weizi (Vicky) Li
Reference: Yuan, Y., Zhang, X., Zhao, J., Shen, F. , Nie, D., Wang, B. , Wang, L., Xing, M. and Hegglin, M. I. (2023) Characteristics, health risks, and premature mortality attributable to ambient air pollutants in four functional areas in Jining, China. Frontiers in Public Health, 11. 1075262. ISSN 2296-2565 doi: 10.3389/fpubh.2023.1075262
Henley faculty authors:
Dr. Bing Wang
Reference: Shen, F. , Hegglin, M. I. , Luo, Y., Yuan, Y., Wang, B. , Flemming, J., Wang, J., Zhang, Y., Chen, M., Yang, Q. and Ge, X. (2022) Disentangling drivers of air pollutants and health risks change during the COVID-19 lockdown in China. npj Climate and Atmospheric Science, 5 (1). 54. ISSN 2397-3722 doi: 10.1038/s41612-022-00276-0
Henley faculty authors:
Dr. Bing Wang

Data Analysis and Experimentation

Making effective improvement decisions requires confidence in using data to understand performance, test assumptions, and identify the actions that will create the greatest impact. Learners develop the analytical skills needed...