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Xian Yang

Research Associate

Data Science Institute

Department of Computing

Imperial College London

South Kensington Campus

London SW7 2AZ, UK



2010-2016             Imperial College London, UK

                             PhD in Computer Science

                             Thesis tile: Analysing datafied life

Brief intro: This thesis focuses on investigating computational methods for analysing data generated from medical research. From the perspective of data type, it proposes analysis methods for the data from the fields of Bioinformatics and medical imaging. From the perspective of research questions, this thesis studies methods for answering five typical questions from simple to complex, which are detecting associations, identifying groups, constructing classifiers, deriving connectivity and building dynamic models. It has successfully demonstrated that applying a method traditionally used in one field to a new field can bring lots of new insights.

2008-2009             University of Bath, UK

                             MSc in Digital Communication (Distinction)

Individual project: Improving WCDMA system in Rayleigh fading channels by using the MIMO scheme to reduce bit error rate and increase system capacity.

2004-2008                 Huazhong University of Science and Technology, China       

                                    BEng in Electronic Information Engineering (First Class)

                             Participated the national university creativity program of moving object detection in compressed media and developing programs to detect moving objects in H.264.

Awarded first class scholarships for undergraduate students in 2005, 2006 and 2007


2016 -                    Research Associate, Data Science Institute, Imperial College London

·         Working on developing the European open science research platform for translational medicine research

2012-2016               Research Assistant, Data Science Institute, Imperial College London

·         Worked on a large EU project for detecting unbiased biomarker of severe asthma

·         Developed data processing pipelines of high throughput mass spectrometry Proteomics and Lipidomics datasets

·         Analysed various Omics and clinical datasets using statistical and machine learning methods

·         Awarded the Trophy for outstanding work on the project in 2013


 Professional Skills

Programming Language: MATLAB, R, Python, JAVA, SQL, html

Operating system: Windows, Mac OS, Linux



[1]     Lei Nie, X. Yang, P. M. Matthews, V. Tomassini, Z. Xu, and Y. Guo. “Inferring Functional Connectivity in fMRI Using Minimum Partial Correlation”. International Journal of Automation and Computing. 2017.

[2]     X. Yang, L. Nie, P. M. Matthews, V. Tomassini, Z. Xu, and Y. Guo, “The Critical Regularization Value: Incorporating Spatial Smoothness to Enhance Signal Detection in Highly Noisy fMRI Data,” in 7th international IEEE/EMBS conference on neural engineering, 2015.

[3]     L. Nie, X. Yang, P. M. Matthews, Z. Xu, and Y. Guo, “Minimum Partial Correlation: An Accurate and Parameter-Free Measure of Functional Connectivity in fMRI,” in 2015 international conference on brain informatics and health, 2015.

[4]     S. Yan, X. Yang, C. Wu, Z. Zheng, and Y. Guo, “Balancing the Stability and Predictive Performance for Multivariate Voxel Selection in fMRI Study,” in The 2014 International Conference on Brain Informatics and Health, 2014.

[5]     S. Yan, X. Yang, C. Wu, Y. Guo, Z. Zheng, and Y. Guo, “Integration of sparse Bayesian learning and random subspace for fMRI Multivariate Pattern Analysis,” in Engineering in Medicine and Biology Society (EMBC), 36th Annual International Conference of the IEEE, 2014.

[6]     L. Nie, X. Yang, I. Adcock, Z. Xu, and Y. Guo, “Inferring cell-scale signalling networks via compressive sensing,” PLoS One, vol. 9, no. 4, 2014.

[7]     X. Yang, Y. Guo, and L. Guo, “An iterative parameter estimation method for biological systems and its parallel implementation,” Concurr. Comput. Pract. Exp., vol. 26, no. 6, pp. 1249–1267, 2014.

[8]     X. Yang, R. Han, Y. Guo, J. Bradley, B. Cox, R. Dickinson, and R. Kitney, “Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA.,” BMC Bioinformatics, vol. 13 Suppl 1, no. Suppl 14, p. S4, 2012.

[9]     A. Holehouse, X. Yang, I. Adcock, and Y. Guo, “Developing a novel integrated model of p38 MAPK and glucocorticoid signalling pathways,” 2012 IEEE Symp. Comput. Intell. Comput. Biol. CIBCB 2012, pp. 69–76, 2012.

[10]   X. Yang, Y. Guo, P. Skipp, and A. Rowe, “Automating Mass Spectrometry Proteomics Analysis,” in Fourth International Conference on Bioinformatics and Computational Biology, 2012.

[11]   Y. Guo and X. Yang, “System Biology Approach to Study Cancer Related Pathways,” in Systems Biology in Cancer Research and Drug Discovery, Springer Netherlands, 2012, pp. 39–67.