Yuyao Wang

I am a Postdoctoral Research Associate in the Department of Biostatistics at Brown University, working with Prof. Larry Han, and a Visiting Postdoctoral Fellow in the Department of Health Care Policy at Harvard Medical School, working with Profs. Alex Luedtke and José R. Zubizarreta.

I received my Ph.D. degree in Mathematics with Specialization in Statistics from University of California San Diego in 2025, where I was advised by Prof. Ronghui (Lily) Xu and collaborating with Dr. Andrew Ying. Before graduate school, I recieved my Bachelor’s degree in Mathematics from Xi’an Jiaotong University.

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Research

My research interests lie at the intersection of survival analysis, causal inference, missing data, and semiparametric theory. I am particularly interested in problems involving censored and truncated data, heterogeneous treatment effects, balancing and weighting approaches, assumption violations, and time-varying treatments. More recently, I have also been developing conformal methods for uncertainty quantification in prediction algorithms, and I am broadly interested in applications in health sciences, education, and psychology.

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, Alexander W. Levis, Shu Yang, Larry Han. (2025) History-aware conformal prediction sets for censored time-to-event outcomes. arXiv:2605.06581. [pdf] [code]
  2. Yuyao Wang, Andrew Ying, Ronghui Xu. (2025) Proximal survival analysis for dependent left truncation. arXiv:2512.21283. [pdf] [code]
  3. 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]
  4. 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. truncProxy: Proximal Weighting Estimation for Dependent Left Truncation
  3. aftR2: R-squared Measure under Accelerated Failure Time (AFT) Models

Presentations

Talks

  • A Liberating Framework from Truncation and Censoring, with Application to Learning Treatment Effects.
    • JICSA Applied Statistics Symposium, 2026. [slides]
  • 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

  • History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes.
    • American Causal Inference Conference (ACIC), 2026. [poster]
    • IMSI workshop: New Horizons on Model Transportability and Data Integration, 2026.
  • Learning Treatment Effects under Covariate Dependent Left Truncation and Right Censoring.
    • New England Rare Disease Statistics (NERDS), 2025.
    • 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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