Yue Chu

Yue Chu

Population health scientist & demographer

Population Health Scientist & Demographer

I study how to measure population health when information is incomplete, heterogeneous, or imperfect, combining demographic, statistical, computational, and AI methods with research software and data infrastructure.

Research Publications Full academic CV 2-page résumé

Research Directions

  • Population Inference with Incomplete and Heterogeneous Data Demographic, statistical, computational, and AI approaches for more reliable population estimates from incomplete, uneven, and heterogeneous evidence.
  • Measurement Processes and Data Quality How data collection, reporting, and classification processes shape the quality, comparability, and interpretation of population evidence.
  • Computational Research Tools and Data Infrastructure Reusable research software and data infrastructure for reproducible analysis, collaborative research, and translation into practice.
23 peer-reviewed publicationsincluding first-, joint-first-, and corresponding-author work Lead-authored population evidencefirst, joint-first, and corresponding-author research WHO Reference Data Archiveplatform manager and core developer 9 surveillance sites, 6 countriesmulti-site mortality analysis, first author

Background

I am a Postdoctoral Fellow at the Institute for Population Research at The Ohio State University. I hold a PhD in Sociology with a minor in Statistics and Demography from Ohio State, an MSPH in Population, Family and Reproductive Health from the Johns Hopkins Bloomberg School of Public Health, and a Bachelor of Medicine in Preventive Medicine from Fudan University. I work with WHO, the Africa Health Research Institute, and international research consortia on mortality measurement, verbal autopsy, and research data infrastructure.

Recent Work

2026

Preprint · medRxiv

Multimodal Artificial Intelligence for Cause-of-Death Assignment From Verbal Autopsy Records: A National Benchmark Study in South Africa

A national benchmark of narrative, structured-data, multimodal, and large-language-model approaches to cause-of-death assignment from verbal autopsy records.

medRxivGitHubProject page

2026

Open-source software

MultimodalVA

Python package implementing narrative, structured-data, and multimodal cause-of-death classifiers.

GitHubProject page

2025

PhD dissertation · arXiv

Leveraging Language Models and Machine Learning in Verbal Autopsy Analysis

Language models and multimodal learning for cause-of-death classification from verbal autopsy narratives and questionnaire data.

arXiv

Selected Publications

2024

Lancet Global Health

Temporal changes in cause of death among adolescents and adults in six countries in Eastern and Southern Africa: a multi-country cohort study using verbal autopsy data.

Yue Chu, M. Marston, A. Dube, C. Festo, E. Geubbels, S. Gregson, K. Herbst, et al.

Lancet Global Health. 2024;12(8):e1278–e1287.

Publication DOI PDF

2022

Journal of Global Health

National and sub-national levels and causes of mortality among 5-19-year-olds in China in 2004-2019: A systematic analysis of evidence from the Disease Surveillance Points System

Y. Liu, Yue Chu, D. Yeung, W. Wang, L. Wang, P. Yin, J. Liu, M. Zhou, L. Liu.

Journal of Global Health. 2022;12:11008.

DOI

2020

Demography

Biases in survey estimates of neonatal mortality: Results from a validation study in urban areas of Guinea-Bissau

S. Helleringer, L. Liu, Yue Chu, A. Rodrigues, A. B. Fisker.

Demography. 2020;57(5):1705–1726.

DOI

2019

Lancet Global Health

National, regional and state all-cause and cause-specific under-five mortality in India in 2000-2015

L. Liu, Yue Chu, S. Oza, D. Hogan, J. Perin, D. G. Bassani, U. Ram, et al.

Lancet Global Health. 2019;7(6):e721–e734.

Publication DOI PDF

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