Dr Xu Huang

Job: VC2020 Lecturer in Economics

School/department: Faculty of Business and Law

Address: Hugh Aston 4.65

T: +44 (0)116 207 8391

E: xu.huang@dmu.ac.uk

W: www.researchgate.net/profile/Xu_Huang7


Personal profile

Dr Xu Huang currently serves as VC2020 Lecturer in Economics at the Faculty of Business and Law. Prior to her appointment at DMU, she worked as Lecturer in Econometrics and Quantitative Methods at Bournemouth University, UK. She is also a Fellow of the Higher Education Academy. Her research area is mainly about developing novel quantitative methods for multivariate analyses like association measure and causality detection based on an advanced time series analysis technique called Singular Spectrum Analysis. Her research interests are multivariate analysis, quantitative method development and causality detection in dynamical complex systems like economics and social science.

Research interests/expertise

Quantitative Method

Multivariate Analysis

Causality Detection

Applied Statistics

Singular Spectrum Analysis

Nonlinear System Analysis

Areas of teaching

Quantitative Method


Mathematics and Statistics


PhD, Bournemouth University, UK

MSc in International Economics, Banking and Finance, Cardiff University, UK

Courses taught

Research Method

Mathematics for Economists

Professional Studies and Quantitative Techniques

Basic Statistical Techniques

Honours and awards

2016 International Institute of Forecasters (IIF) Travel Award Grant

2015 Santander University Postgraduate Research Scholarship

2014 Bournemouth University Postgraduate Development Fund Award

2013 Bournemouth University PhD Full Scholarship

Professional licences and certificates

HEA Fellow (2016)

Conference attendance

Huang, X. (2017). Causality between oil price and tourist arrivals: evidences from advanced nonparametric causality detection methods. In: 37th International Symposium on Forecasting, June 25-28, 2017. Cairns, Australia.

Huang, X. (2016). Novel Non-Parametric Dynamic Causality Detection Methods. In: 36th International Symposium on Forecasting, 19 – 22 June, 2016 Santander, Spain.

Huang, X. (2016). Causality between Sunspot Number and Global Temperature: Evidences from Novel Non-Parametric Dynamic Causality Detection Methods. In: UK Causal Inference Meeting 2016, 11 – 15 April, London, UK.

Huang, X. (2014). Causality between Alcohol and Crime. In: 34th International Symposium on Forecasting, 29 June – 2 July, 2014 Rotterdam, Netherlands.

Recent research outputs

  • Hassani, H., Huang, X. and Ghodsi, M. (2017). Big Data and Causality. Annals of Data Science. DOI: 10.1007/s40745-017-0122-3
  • Huang, X., Hassani, H., Ghodsi, M, Mukherjee, Z. and Gupta, R. (2017). Do trend extraction approaches affect causality detection in climate change studies? Physica A: Statistical Mechanics and its Applications, 469, 604-624. Elsevier.
  • Ghodsi, Z., Huang, X. and Hassani, H. (2017). Causality analysis detects the regulatory role of maternal effect genes in the early Drosophila embryo. Genomics Data, 11, 20-38.
  • Hassani, H., Huang, X., Gupta, R. and Ghodsi, M. (2016). Does sunspot numbers cause global temperatures? A reconsideration using non-parametric causality tests. Physica A: Statistical Mechanics and its Applications, 460, 54-65. Elsevier.
  • Hassani, H., Huang, X., Silva, E. and Ghodsi, M. (2016). A review of data mining applications in crime. Statistical Analysis and Data Mining: the ASA Data Science Journal, 9(3), 139-154. Wiley.
  • Huang, X., Ghodsi, M. and Hassani, H. (2016). A Novel similarity measure based on eigenvalue distribution. Transactions of A. Razmadze Mathematical Institute, 170(3), 352-362. Elsevier.
  • Huang, X. and Ghodsi, M. (2016). A novel mutual association measure based on eigenvalue-based criterion. International Journal of Energy and Statistics, 4(04), 1650017.
  • Ghodsi, M. and Huang, X. (2015). Causality between energy poverty and economic growth in Africa: Evidences from time and frequency domain causality test. International Journal of Energy and Statistics, 3(04), 1550020.

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