Bio

I am a PhD student in the Statistics and Data Sciences Department at UT Austin studying under the supervision of Dr. Layla Parast. My research focuses on nonparametric methods in surrogate marker modeling and preventing the surrogate paradox.

Education

University of Texas at Austin | Austin, TX

Ph.D. in Statistics | Expected May 2026

University of California, Berkeley | Berkeley, CA

B.A. in Data Science | May 2021

Research Experience

Department of Statistics and Data Sciences, University of Texas at Austin | Graduate Researcher | 2023 - 2025

  • Proposed a nonparametric framework to assess assumptions required in current surrogate marker validation techniques to preclude the surrogate paradox
  • Demonstrated new methodology on simulated data in different, and illustrated methods on diabetes clinical trial data
  • Created R package SurrogateParadoxTest which implements method for future analyses (CRAN | GitHub)

Los Alamost National Laboratory | Graduate Researcher | May 2023 - August 2023

  • Worked under the supervision of Dr. John Tipton to develop a model for forecasting mosquito abundance by accounting for sampling effort using temporal chnage of support
  • Used for an epidemiological model for predicting cases of mosquito-borne diseases such as denggue and West Nile Virus

Department of Statistics and Data Sciences, University of Texas at Austin | Graduate Researcher | Summer 2022 - Spring 2023

  • Worked under the supervision of Dr. Kate Calder using spatial point processes to model crime in Columbus, Ohio
  • Used spatially smoothed and areal neighborhood covariates as model inputs

Industry Experience

Facebook | Software Engineering Intern | May 2020 - August 2020

  • Implemented data mining algorithm for internal tool for diagnosing error messages
  • Coded in python and FBthrift to serialize between different languages

Facebook | Facebook University Intern | May 2019 - August 2019

  • Developed an app designed for showing users news articles from different ends of the political spectrum
  • Coded in Objective-C to implement app features

Teaching Experience

Teaching Assistant | University of Texas at Austin | Fall 2021 - Current

  • SDS 384: Design Principles and Causal Inference | Fall 2024
  • SDS 383: Advanced Predictive Models | Spring 2023
  • SDS 313: Introduction to Data Science | Fall 2023
  • SDS 302F: Foundations of Data Analysis | Fall 2022, Fall 2022
  • SDS 321: Introduction to Probability and Statistics | Spring 2022

Volunteer Instructor | Texas Prison Education Initiative (through UT Extension) | Spring 2022 - Current

  • Math 305G: Precalculus | Fall 2023, Fall 2024
  • College Prep Math | Spring 2022, Fall 2022

Assistant Instructor | University of Texas at Austin | Spring 2024

  • SDS 320E: Elements of Statistics

Undergraduate Teaching Assistant | University of California, Berkeley | Spring 2020 - Spring 2022

  • Stat 88: Probability and Mathematical Statistics for Data Science | Fall 2020, Spring 2021
  • Stat 140: Probability for Data Science | Spring 2020

Other things!

I'm into a lot of stuff. Right now, I like triathlon, hiking, backpacking, etc. I also love books - you can find my goodreads book reviews here. I am also an ethical and environmental vegan, which means that I am against the exploitation of animals for human gain.

Emily Hsiao


Bio

I am a PhD student in the Statistics and Data Sciences Department at UT Austin studying under the supervision of Dr. Layla Parast. My research focuses on nonparametric methods in surrogate marker modeling and preventing the surrogate paradox.

Education

University of Texas at Austin | Austin, TX

Ph.D. in Statistics | August 2021 - Present

University of California, Berkeley | Berkeley, CA

B.A. in Data Science | May 2021