Lai (Catherine) Xu
Los Angeles,CA
Summary
Biostatistician with PhD training in quantitative methods and strong expertise in statistical modeling, robust estimation, and high-dimensional data analysis. Experienced in developing and applying advanced biostatistical and computational methods to complex biological, behavioral, and population-level data. Proven ability to support study design, data cleaning, modeling, and interpretation using reproducible statistical workflows. Strong programming background in R and Python with experience across academic research and statistical consulting settings.
Overview
9
9
years of professional experience
Work History
Researcher
University of Southern California
Los Angeles, CA
08.2022 - Current
- Leveraged natural language processing and MRP modeling to incorporate social media data for improved subnational inference
- Developed robust multivariate regression methods to detect, classify, and manage distinct outlier structures in high-dimensional datasets using projection distance–based approaches
- Implemented robust measurement invariance and alignment optimization techniques to support approximate invariance across heterogeneous populations
- Utilized robust principal component analysis (PCA) to enhance interpretation of complex data structures while achieving efficient dimensionality reduction without loss of critical information
Teaching Assistant
University of Southern California
01.2017 - 05.2025
- Experimental Design, University of Southern California, Jan 2025 – May 2025
- Introduction to Psychology, University of Southern California, Aug 2024 – Dec 2024
- Non-Experimental Research Design, University of Southern California, Jan 2023 – May 2022
- Statistics, University of Southern California, Aug 2022 – Dec 2022
- Classic & Modern Statistical Methods I, University of Southern California, Aug 2021 – May 2022
- Statistics, University of Southern California, Jan 2020 – May 2020
- Introduction to Psychology, University of Southern California, Aug 2019 – Dec 2019
- Probability & Statistics in Psychology, University of Washington, Jan 2017 – Mar 2018
- Statistical Inference in Psychology, University of Washington, Jan 2017 – Mar 2018
Statistical Consultant / Data Scientist
GC3, University of Southern California
Los Angeles, CA
08.2021 - 05.2022
- Conducted survival analyses, including Kaplan–Meier estimation, log-rank testing, and Cox proportional hazards regression, to evaluate time-to-event outcomes and covariate effects
- Applied ANCOVA and regression-based adjustment methods to compare group differences while controlling for baseline and confounding variables
- Applied appropriate inferential and multivariate statistical methods, including regression modeling, experimental and non-experimental designs
- Assisted researchers with power analysis and sample size considerations using G*Power and related tools
- Programmed custom R and Python functions to automate analyses, streamline workflows, and ensure reproducibility
- Supported statistical reporting, result interpretation, and data visualization for manuscripts and presentations
- Implemented analyses and reporting pipelines using SAS and R, ensuring reproducibility and efficient data processing
Research Assistant
Gire Lab, University of Washington
Seattle, WA
03.2018 - 06.2019
- Supported biological and neuroscience research through data cleaning, statistical modeling, and visualization in R and MATLAB
- Assisted with experimental data analysis and interpretation to support peer-reviewed publications
- Helped develop standard operating procedures (SOPs) to ensure data quality, consistency, and reproducibility
- Collaborated with multidisciplinary teams to translate experimental data into statistically valid conclusions
Research Assistant
Cognitive & Cortical Dynamics Lab, UW
Seattle, WA
05.2017 - 09.2018
- Collected and analyzed human EEG data, ensuring protocol compliance and high data quality
- Developed Python scripts to automate data preprocessing and statistical analysis pipelines
- Conducted exploratory and confirmatory analyses to support hypotheses in cognitive neuroscience studies
Education
Ph.D. - Quantitative Methods & Computational Psychology
University of Southern California
Master of Arts - Quantitative Methods & Computational Psychology
University of Southern California
Bachelor of Science - Psychology
University of Washington
Skills
Software & Programming: R, Python,SAS, SQL, SPSS, MATLAB
Publications
Wilcox, R. & Xu, L. (2022). Regression: Identifying Good and Bad Leverage Points. International Journal of Statistics and Probability. 12. 1. 10.5539/ijsp.v12n1p1.
Xu, L. & Wilcox, R. (2021). Comparing Skipped Correlations: The Overlapping Case. Manuscript submitted for publication
Lewis, S. M., Xu, L., Rigolli, N., Tariq, M. F., Suarez, L. M., Stern, M., Seminara, A., & Gire, D. H. (2021). Plume Dynamics Structure the Spatiotemporal Activity of Mitral/Tufted Cell Networks in the Mouse Olfactory Bulb. Frontiers in cellular neuroscience, 15, 633757. https://doi.org/10.3389/fncel.2021.633757
Timeline
Researcher
University of Southern California
08.2022 - Current
Statistical Consultant / Data Scientist
GC3, University of Southern California
08.2021 - 05.2022
Research Assistant
Gire Lab, University of Washington
03.2018 - 06.2019
Research Assistant
Cognitive & Cortical Dynamics Lab, UW
05.2017 - 09.2018
Teaching Assistant
University of Southern California
01.2017 - 05.2025
Ph.D. - Quantitative Methods & Computational Psychology
University of Southern California
Master of Arts - Quantitative Methods & Computational Psychology
University of Southern California
Bachelor of Science - Psychology
University of Washington