• PhD student, Statistical Genetics, The University of Queensland, 2020-2023
  • MSc, Applied Statistics, Renmin University of China, 2014-2016
  • BSc, Animal Science, China Agricultural University, 2010-2014

Honors & Awards

  • UQ Research Training Scholarship, 2020-2023
  • Scholarship of Academic Excellence, China Agricultural University, 2011, 2012
  • Outstanding Student Leader Awards, China Agricultural University, 2012
  • Fonterra Dairy Scholarship, China Agricultural University, 2011

Publications (Google Scholar)

Work Experience

  • Data Scientist, Percent, 2017.5-2018.10

    I was a data scientist at Percent, a leading big data company in China. My responsibilities included developing statistical model for population projection and mastered knowledge in demography, analyzing malaria incidence dataset in Africa with spatial statistical methods. I also learned RNN, LSTM for natural language processing.

  • Algorithm Engineer, WeGene, 2016.6-2017.4

    At WeGene, the largest DTC company in China, I developed algorithm and shiny apps for ancestry analysis and optimized the efficiency of the R code. Undertook task of analyzing Axiom genotyping array data. Investigated the accuracy of APoE genotypes derived from Axiom array.


  • radmixture(An R package for individual ancestry analysis)


  • Algorithm for ancestry analysis and its performance optimization (slides)

    Presented at the 10th China R conference. East China Normal University, Shanghai, China. December, 2016

  • Sentiment analysis using product review data (slides)

    Presented at R Users Group meetup. Shanghai, China. July, 2017

Professional Skills

  • R user with 7 years’ experience and 3 years’ of R engineering experience. Familiar with the workflow of developing R package and R high performance programming.
  • Languages and tools used often: R, python, bash, Git, awk, sed, SAS, C (mainly focuses on improving speed of R code), HTML, CSS, JavaScript, MySQL, Julia, Scala.
  • Advanced knowledge in shiny app development.
  • Web scraping with scrapy and rvest.
  • Good knowledge of genomics and molecular biology. Familiar with PLINK and Affymatrix Axiom genotyping workflow.