Yuyao Wang

I am a postdoctoral research fellow in the Department of Public Health and Health Sciences at Northeastern University, working with Prof. Larry Han.

I received my PhD degree in mathematics with a specialization in statistics in 2025 at University of California San Diego, where I was advised by Prof. Ronghui (Lily) Xu and collaborating with Dr. Andrew Ying. I also received mentorship from Dr. Kendrick Li during my 2024 summer internship at St. Jude Children's Research Hospital.

Before graduate school, I recieved my bachelor’s degree in mathematics from Xi’an Jiaotong University. I also visited Georgia Institute of Technology and University of Alberta as a visiting student during my undergrad.

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Research

My research is in causal inference, survival analysis, missing data problems, and semiparametric theory, particularly in addressing challenges related to left truncation, a common source of selection bias (sampling bias) for time-to-event data.

I am broadly interested in topics in causal inference, survival analysis, and missing data problems, especially in selection bias, heterogeneous treatment effects, balancing weighting approaches, assumption violations, continuous treatment, and time-varying treatment. I am also interested in semiparametric and nonparametric theory, high dimensional statistics, and conformal inference.

I am interested in applications in health and social sciences.

Publications
  1. Yuyao Wang, Andrew Ying, Ronghui Xu. (2024) Doubly robust estimation under covariate-induced dependent left truncation. Biometrika, 111(3), 789-808. [pdf] [code] [R package]

    (This paper won the student paper competition award for 2023 Lifetime Data Science Conference)

  2. Yingwei Peng, Yuyao Wang, Ronghui Xu. (2023) Measures of explained variation under the mixture cure model for survival data. Statistics in Medicine, 42(3), 228-245. [pdf]
ArXiv Preprints and Working Papers
  1. Yuyao Wang, Andrew Ying, Ronghui Xu. (2024) A liberating framework from truncation and censoring, with application to learning treatment effects. arXiv:2411.18879. [pdf] [code]
  2. Yuyao Wang, Andrew Ying, Ronghui Xu. (2025+) Proximal survival analysis for dependent left truncation. (In preparation).
  3. Lon R. White, Yuyao Wang, Lenore Launer, Lucia Seale, Marla Berry, Margaret Flannagan, Thomas J. Montine, Ronghui Xu. (2024+) Midlife dietary selenium and Okinawan ancestry are independently associated with less severe Alzheimer neuropathology at autopsy in Japanese-American men. Submitted to Journal of Alzheimer's Disease.
R packages
  1. truncAIPW: Doubly Robust Estimation under Covariate-Induced Dependent Left Truncation
  2. aftR2: R-squared Measure under Accelerated Failure Time (AFT) Models

Presentations

Talks

  • Proximal Survival Analysis for Dependent Left Truncation.
    • Joint Statistical Meetings (JSM), 2025. [slides]
  • Learning Treatment Effects under Covariate Dependent Left Truncation and Right Censoring.
    • Lifetime Data Science Conference, 2025.
    • Online Causal Inference Seminar (OCIS), November 5, 2024. [slides] [video]
    • Biostatistics Seminar, Department of Population Medicine, Harvard Pilgrim Health Care Institute, 2024.
    • Causal Inference Seminar, Boston University, 2024.
    • Causal Group Seminar, Carnegie Mellon University, 2024.
    • Joint Statistical Meetings, 2024.
    • Southern California Applied Mathematics Symposium, 2024.
  • Doubly Robust Estimation under Covariate-induced Dependent Left Truncation.

Posters

  • Learning Treatment Effects under Covariate Dependent Left Truncation and Right Censoring.
    • Public Health Research Day at UCSD, 2025. [poster]
  • Doubly Robust Estimation of Treatment Effects under Covariate Dependent Left Truncation and Right Censoring.
    • American Causal Inference Conference (ACIC), 2024. [poster]
    • Public Health Research Day at UCSD, 2024.
  • Multiply Robust Estimation of Treatment Effect for Time-to-event Outcome under Dependent Left Truncation.
    • American Causal Inference Conference (ACIC), 2023. [poster]
    • Public Health Research Day at UCSD, 2023.
  • Semiparametric Estimation for Non-randomly Truncated Data.
    • American Causal Inference Conference (ACIC), 2022. [poster]
    • Public Health Research Day at UCSD, 2022.

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