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Xiyun Jiao
Assistant Proffesor
0755-88015734

Brief Biography

Xiyun Jiao, Ph.D., is an Assistant Professor at Department of Statistics and Data Science of Southern University of Science and Technology (SUSTech). She obtained her Ph.D in statistics in 2016 from Imperial College London, UK. She was a postdoctoral research fellow at University College London, UK from 2017 to 2020.  Her research focus is on Computational statistics, Bayesian statistics, Markov chain Monte Carlo algortihms, Statistical methods in Population Genetics, and she has published papers in top tier journals like Journal of Computational and Graphical Statistics, Journal of Econometrics, Systematic Biology, etc.

 

Research Interests

Computational statistics

Bayesian statistics

Markov chain Monte Carlo algortihms

Statistical methods in Population Genetics

 

 

Professional Experience

2020.09 - present          Assistant Professor

Department of Statistics and Data Science, Southern University of Science and Technology

2017.05 - 2020.05         Postdoctoral Research Fellow

Imperial College London, UK

2019.05 - 2019.05         Teaching Assistant

Computational molecular evolution workshop, Hinxton, UK

 

 

Education

2012.11 - 2016.12        Ph.D. in Statistics

Imperial College London, UK

2010.09 - 2012.07        Master in Statistics

Katholieke Universiteit Leuven, Belgium

2006.08 - 2010.07        Bachelor in Mathematics

Tisinghua University, China

 

Publications

  1. Jiao, X. and Yang, Z.; Defining species despite gene flow. Systematic Biology, pages in press.

  2. Jiao, X., Flouri, T., Rannala, B., and Yang, Z.; The impact of cross-species gene flow on species tree estimation. Systematic Biology, pages in press.

  3. Jiao, X. and van Dyk, D. A.; A corrected and more efficient suite of MCMC samplers for the multinomal probit model. Journal of Econometrics, to appear.

  4. Flouri, T., Jiao, X., Rannala, B., and Yang, Z.; A Bayesian implementation of the multispecies coalescent model with introgression for comparative genomic analysis. Molecular Biology and Evolution, 37(4), 1211-1223.

  5. Flouri, T., Jiao, X., Rannala, B., and Yang, Z. (2018). Species tree inference with BPP using genomic sequences and the multispecies coalescent. Molecular Biology and Evolution, 35 (10), 2585-2593.

  6. Shariff, H., Jiao, X., Dhawan, S., Leibundgut, B., Trotta, R., and van Dyk, D. A. (2016). Standardizing Type Ia supernovae using near infrared rebrightening timing. Monthly Notices of the Royal Astronomical Society, 463, 4311-4316.

  7. Shariff, H., Jiao, X., Trotta, R., and van Dyk, D. A. (2016). BAHAMAS: New SNIa analysis reveals inconsistencies with standard cosmology. The Astrophysical Journal, 827, No. 1.

  8. Jiao, X., van Dyk, D. A., Trotta, R., and Shariff, H. (2016). The effciency of next-generation Gibbs-type samplers: An illustration using a hierarchical model in cosmology. New Developments in Statistical Modeling, Inference and Application: Selected Papers from the 2014 ICSA/KISS Joint Applied Statistics Symposium in Portland, OR, 167-184.

  9. van Dyk, D. A. and Jiao, X. (2015). Metropolis-Hastings within partially collapsed Gibbs samplers. Journal of Computational and Graphical Statistics, 24, 301-327.


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