• B.S, Statistics, Nankai University, China, 2013
  • M.S, Statistics, Michigan State University, USA, 2015, GPA 4.0/4.0
  • Ph.D, Statistics, Michigan State University, USA, 2020, GPA 4.0/4.0


  • Jun. 2020 - Current, Applied Research Data Scientist, Forecasting at Linked[IN] Corporation.
  • Aug. 2019 - Jun. 2020, Research assistant, Department of Statistics and Probability, Michigan State University
    • Research neural networks in high-dimensional low sample-size (HDLSS) data problems.
  • May. 2019 - Aug. 2019, Applied Researcher, Forecasting [IN]tern at Linked[IN] Corporation.
    • Design and use machine learning models to forecast site traffic and build pipeline.
  • Aug. 2013 - May. 2019, Teaching assistant, Department of Statistics and Probability, Michigan State University
    • Lead undergraduate statistics recitations and labs
    • Work in the statistics helproom
    • Design and teach undergraduate courses as a lecturer


Programming skills

  • Expert in Python, R and LaTeX
  • Proficiency in Matlab, Linux, Git and SQL
  • Experience in C++, IOS (Swift), Scala, Spark, SAS, Minitab and Gurobi
  • Also uses Microsoft Office

Professional skills

  • Machine learning: regression, classification, clustering, dimensionality reduction, time series forecasting, neural networks, tree methods, ensemble
  • Statistics: confidence intervals, hypothesis testing, A/B testing, survival analysis, design of experiment, Bayesian modeling, stochastic process, spatial statistics
  • Computer science: data structure, optimization, algorithm


  • University Fellowship, Nankai University, 2009
  • Honorable mention prize, North America Mathematical Contest in Modeling, 2012
  • Scientific and Creative award, Nankai University, 2012
  • William L. Harkness Award, for excellence in teaching, Michigan State University, 2017
  • SAMSI deep learning workshop travel award, SAMSI, 2019
  • IEEE 6th DSAA travel award, IEEE, 2019