Experience

  1. Data Scientist

    Institute of Environmental Science and Research (ESR), New Zealand

  2. Big Data Analytics Internship

    Vodafone New Zealand Limited

Education

  1. PhD in Statistics

    University of Auckland

    Thesis on Multiple Imputation Through Statistical Learning.

    • Supervisors: Prof Thomas Lumley, Assoc. Prof Beatrix Jones
    Read Thesis

  2. B.Sc (Honours) in Statistics, First Class Honours

    University of Auckland

    GPA 8.875 out of 9

    Honours Project: Optimal Path in Random Graphs

    • Supervisor: Dr Jesse Goodman

    Courses included:

    • Probability Theory, Bayesian Inference, Modern Applied Statistics
    • Machine Learning, Data mining, Statistical Computing

  3. B.Sc in Mathematics and Statistics

    University of Auckland

    GPA 8.75 out of 9

    Summer Research in Mathematics: Number Theory and Cryptography

    • Supervisor: Prof Steven Galbraith

    Courses included:

    • Real Analysis, Algebraic Structures, Partial Differential Equations, Stochastic Processes
    • Statistical Inference, Statistical Theory, Statistical Modelling, Time Series
Awards
University of Auckland Doctoral Scholarship (2019-2022)
University of Auckland ∙ March 2019
Highly Commended Student Talk at 2020 NZSA Conference
The New Zealand Statistical Association ∙ November 2020
Best Student Talk at 2020 NZSA Conference
The New Zealand Statistical Association ∙ November 2019
Senior Scholar Award
University of Auckland ∙ December 2017
Awarded for achieving the highest overall grades in the degree programme
Summer Research Scholarship
University of Auckland ∙ November 2017
Top 20 Statistics Student
University of Auckland ∙ December 2017
Top 20 Statistics Student
University of Auckland ∙ December 2016
The Ivan Reilly Prize
University of Auckland ∙ December 2016
Recognised for being the top performing student in MATHS 250
First in Course Awards (2016-2018)
University of Auckland ∙ December 2018
  • STATS 760 (A Survey of Modern Applied Statistics)
  • STATS 310 (Introduction to Statistical Inference)
  • MATHS 255 (Principles of Mathematics)
  • MATHS 250 (Advancing Mathematics 2)
  • STATS 125 (Probability and its Applications)
Skills & Hobbies
Technical Skills
R
Python
SQL
Hobbies
Singing
Watercolour
Photography
Languages
90%
English
100%
Cantonese
95%
Mandarin