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. José R. Zubizarreta and Alex Luedtke.

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 collaborated with Dr. Andrew Ying. Before graduate school, I received 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, Alexander W. Levis, Shu Yang, Larry Han. (2026) History-aware conformal prediction sets for censored time-to-event outcomes. arXiv:2605.06581. Accepted at NeurIPS. [pdf] [code]
  2. 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)

  3. 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. (2025) Proximal survival analysis for dependent left truncation. arXiv:2512.21283. [pdf] [code]
  2. 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]
  3. Jiyue Qin, Yuyao Wang, Ronghui Xu. (2026) Doubly Robust Estimation under Covariate Dependent Censoring in Semi-Competing Risks Data. arXiv:2609.32311. [pdf]
  4. Yuyao Wang, Alexander W. Levis, Shu Yang, Larry Han. (2026) Risk-Controlling Prediction Sets for Dynamic Survival Prediction under Right Censoring. (Work in progress)
  5. Zhiyue Mo, Yuyao Wang, Larry Han. (2026) Cross-fitted doubly robust estimation of smooth marginal causal contrasts: a tutorial with vaccine-trial applications. (Work in progress)
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

  • History-Aware Conformal Prediction Sets for Censored Time-to-Event Outcomes.
    • Joint Statistical Meetings (JSM), 2026. [slides]
    • IMS New Researcher Conference, 2026 (lightning talk).
  • A Liberating Framework from Truncation and Censoring, with Application to Learning Treatment Effects.
    • ICSA 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]
    • STAI-X: Statistics and Trustworthy AI for Cross (X)-Domain Acceleration, 2026.
    • 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) Workshop, 2025. (Best Poster Award)
    • 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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