Shuting Liao

Shuting Liao

PhD candidate in Biostatistics

University of California-Davis

I am a 4th year Ph.D. student in the Graduate Group in biostatistics (GGB) at the University of California-Davis. I’m under the supervision of Prof. Fushing Hsieh and Prof. Debashis Paul. Prior to UCD, I completed my M.S. in statistics at the University of Michigan-Ann Arbor. I particularly enjoy uncovering the stories that underlie complex real-world data. I’m broadly interested in Machine Learning, data mining, (parametric and nonparametric) statistical modeling, and sampling procedures.

Interests

  • ANOVA
  • Statistical Modeling
  • Bootstrap Sampling
  • Bayesian
  • Machine Learning
  • Visualization

Education

  • Ph.D. in Biostatistics, 2018 - (in progress)

    University of California-Davis

  • M.S. in Statistics, 2016 - 2018

    University of Michigan-Ann Arbor

  • B.S. in Mathematics, 2012 - 2016

    Sichuan University

Projects

Publications

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Analysis of variability of functionals of growth trajectories based on limited data

Develop a statistical framework for analyzing the variability in smooth, possibly nonlinear, functionals associated with a set of growth trajectories measured under different experimental conditions.
PDF

Taming the pandemic by doing the mundane

A study on controlling the COVID-19 pandemic
PDF

The geometry of colors in van Gogh's Sunflowers

Paintings fade like flowers: van Gogh’s prediction on the impact of age on paintings came true for most of his paintings. We have …
Shuting Liao, Patrice Koehl, Jennifer Schultens, Fushing Hsieh
PDF Project

Color-complexity enabled exhaustive color-dots identification and spatial patterns testing in images

Targeted color-dots with varying shapes and sizes in images are first exhaustively identified, and then their multiscale 2D geometric …
Shuting Liao, Li-Yu Liu, Ting-An Chen, Kuang-Yu Chen, Fushing Hsieh
PDF

Inference on the dynamics of the COVID pandemic from observational data

Apply a nonparametric stochastic dynamics model in discrete time for describing the evolution of the COVID-19 pandemic through a system of linear Ordinary Difference Equations that represents the various states or stages of the disease.
PDF Code

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