Dr. YANG, Xian
Dr. YANG, Xian

B.Eng., M.Sc., Ph.D.
Assistant Professor, Department of Computer Science


Dr. Xian Yang is currently an Assistant Professor at the Department of Computer Science, Hong Kong Baptist University. Before joining HKBU, Dr Xian Yang worked as a research associate in Data Science Institute at Imperial College London from 2012 to 2018, and since 07/2019 as a research fellow. Dr Xian Yang has taken part in many cross European research projects, such as UBIOPRED (severe asthma subtyping), eTRIKS (knowledge management platform for translational medicine), Optimise (multiple sclerosis disease prognosis and treatment) and iHealth (clinical treatment pathway optimisation). Her main role in these projects was developing data analysis/machine learning methods to analyse and construct predictive models from Omics, clinical and other datasets such as survey data, imaging data and text data. She has also been working as a researcher in Microsoft Research Asia from 09/2018 to 07/2019, carrying out research in AI for Cloud. Dr Xian Yang received her PhD degree in 2016 from the department of computing at Imperial College London. Her research interests are artificial intelligence in healthcare, modern medicine and cloud computing. Her work has been published in several top-tier conferences/journals, such as WWW, FSE, and Bioinformatics.

Research Interests

  • Medical AI
  • Natural Language Processing for electronic health records
  • Artificial Intelligence for Cloud
  • Bayesian inference
  • Network Embedding

Selected Publications

  • Y. Chen, X. Yang, et al. “Identifying Linked Incidents in Large-scale Online Service System”, The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2020
  • J. Zhang, X. Zhang, K. Sun, X. Yang, C. Dai, and Y. Guo, “Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records”, 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 2019
  • X. Zhang, J. Zhang, K. Sun, X. Yang, C. Dai, and Y. Guo, “Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification”, (short paper) 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 2019
  • Y. Chen, X. Yang, et al. “Outage Prediction and Diagnosis for Cloud Service Systems”, (short paper) WWW2019: The Web Conference, 2019.
  • J. Perotin, J. Schofield, S. Wilson, J. Ward, J. Brandsma, F. Strazzeri, A. Bansal, X. Yang, et al. “Epithelial dysregulation in obese severe asthmatics with gastro-oesophageal reflux”, European Respiratory journal, 2019.
  • J. Schofield, D. Burg, B. Nicholas, F. Strazzeri, J. Brandsma, D. Staykova, C. Folisi, A. Bansal, X. Yang, et al. “Stratification of asthma phenotypes by airway proteomic signatures”, Journal of Allergy and Clinical Immunology, 2019.
  • J. Brandsma, V. Goss, X. Yang, et al. “Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers”, Metabolomics Journal, 2018.
  • B. Meulder, D. Lefaudeux, A. Bansal, A. Mazein, A. Chaiboonchoe, H. Ahmed, I. Balaur, M. Saqi, J. Pellet, S. Ballereau, N. Lemonnier, K. Sun, I. Pandis, X. Yang, et al. “A computational framework for complex disease stratification from multiple large-scale datasets”, BMC System Biology, 2018.
  • D. Burg, J. Schofield, J. Brandsma, D. Staykova, C. Folisi, A. Bansal, B. Nicholas, X. Yang, et al. “Large-scale label-free quantitative mapping of the sputum proteome”, Journal of Proteome Research, 2018.
  • X. Yang, Y. Guo and W. Pan, “Sparse Bayesian classification and feature selection for biological expression data with high correlations”, PloS One, vol. 12, no. 12, 2017.