Haidong Lu

Yale School of Medicine

367 Cedar Street

New Haven, CT 06510

I am an Assistant Professor of Medicine and Epidemiology at Yale, with a primary appointment in the Section of General Internal Medicine and a secondary appointment in the Department of Chronic Disease Epidemiology at the Yale School of Public Health. I am affiliated with the Yale Program in Addiction Medicine, the Yale Institute for Foundations of Data Science, and the YSPH Public Health Modeling Unit. I also serve as a Research Statistician at the VA Connecticut Healthcare System.

I lead the LU Causal Intelligence & Data Lab (LUCID Lab). My research bridges epidemiology, statistics, and data science — developing and applying causal inference methods to observational health data to generate real-world evidence that can inform clinical decision-making. Substantive areas include substance use, HIV/AIDS, and pharmacoepidemiology / comparative effectiveness research. Methodological interests include target trial emulation, selection bias, generalizability and representativeness, heterogeneous treatment effects, and machine learning for causal questions.

I received my PhD in Epidemiology (with a minor in Biostatistics) from the UNC Gillings School of Global Public Health in 2020, where I was advised by Stephen R. Cole and Daniel Westreich. I then completed postdoctoral training at Yale with Gregg Gonsalves. My research is currently supported by an NIH/NIDA K99/R00 Pathway to Independence Award.

I am always happy to hear from prospective students, postdocs, and collaborators — please reach out by email.

news

Mar 2026	New paper — Toward a Clearer Definition of Per-protocol Effect — in press at Epidemiology.
Jan 2026	Constructing G-computation Estimators: Two Case Studies in Selection Bias (with Paul Zivich) published in Epidemiology.
Aug 2025	R00 phase of my NIH/NIDA K99/R00 Pathway to Independence Award activated — Evaluating and Optimizing Care for Opioid Use Disorder using a Structured Data-Science Approach.
Feb 2025	Promoted to Assistant Professor of Medicine and Epidemiology at Yale, launching the LU Causal Intelligence and Data Lab (LUCID Lab).
Dec 2024	Named Exemplary Reviewer of the Year by Epidemiology and Runner-up, Early Career Best Paper, American College of Epidemiology.

selected publications

Epidemiology

Toward a Clearer Definition of Per-protocol Effect

Haidong Lu, Buket Öztürk Esen, and Rachael K. Ross

Epidemiology, 2026

In press

Bib

@article{lu2026perprotocol,
  title = {Toward a Clearer Definition of Per-protocol Effect},
  author = {Lu, Haidong and Esen, Buket \"{O}zt\"{u}rk and Ross, Rachael K.},
  journal = {Epidemiology},
  year = {2026},
  note = {In press},
}

Eur J Epidemiol

Machine Learning versus Logistic Regression for Propensity Score Estimation: A Trial Emulation Benchmarked against the PARADIGM-HF Randomized Trial

Kaicheng Wang, Lindsey Rosman, and Haidong Lu

European Journal of Epidemiology, 2026

Bib HTML

@article{wang2026ml,
  title = {Machine Learning versus Logistic Regression for Propensity Score Estimation: A Trial Emulation Benchmarked against the PARADIGM-HF Randomized Trial},
  author = {Wang, Kaicheng and Rosman, Lindsey and Lu, Haidong},
  journal = {European Journal of Epidemiology},
  year = {2026},
}

IJE

Revisiting Representativeness

Haidong Lu, Paul N. Zivich, Jacqueline E. Rudolph, and 3 more authors

International Journal of Epidemiology, 2025

Bib

@article{lu2025representativeness,
  title = {Revisiting Representativeness},
  author = {Lu, Haidong and Zivich, Paul N. and Rudolph, Jacqueline E. and Liew, Zeyan and Mukherjee, Bhramar and Li, Fan},
  journal = {International Journal of Epidemiology},
  volume = {54},
  number = {1},
  pages = {dyaf003},
  year = {2025},
}

IJE

Four Targets: An Enhanced Framework for Guiding Causal Inference from Observational Data

Haidong Lu, Fan Li, Catherine R. Lesko, and 6 more authors

International Journal of Epidemiology, 2025

Bib

@article{lu2025fourtargets,
  title = {Four Targets: An Enhanced Framework for Guiding Causal Inference from Observational Data},
  author = {Lu, Haidong and Li, Fan and Lesko, Catherine R. and Fink, David S. and Rudolph, Kara E. and Harhay, Michael O. and Rentsch, Christopher T. and Fiellin, David A. and Gonsalves, Gregg S.},
  journal = {International Journal of Epidemiology},
  volume = {54},
  number = {1},
  pages = {dyaf003},
  year = {2025},
}

Epidemiology

Toward a Clearer Definition of Selection Bias When Estimating Causal Effects

Haidong Lu, Stephen R. Cole, Chanelle J. Howe, and 1 more author

Epidemiology, 2022

Bib

@article{lu2022selection,
  title = {Toward a Clearer Definition of Selection Bias When Estimating Causal Effects},
  author = {Lu, Haidong and Cole, Stephen R. and Howe, Chanelle J. and Westreich, Daniel},
  journal = {Epidemiology},
  volume = {33},
  number = {5},
  pages = {699--706},
  year = {2022},
}

CID

Clinical Effectiveness of Integrase Strand Transfer Inhibitor-based Antiretroviral Regimens among Adults with HIV: A Collaboration of Cohort Studies in the United States and Canada

Haidong Lu, Stephen R. Cole, Daniel Westreich, and 4 more authors

Clinical Infectious Diseases, 2021

Bib

@article{lu2021insti,
  title = {Clinical Effectiveness of Integrase Strand Transfer Inhibitor-based Antiretroviral Regimens among Adults with {HIV}: A Collaboration of Cohort Studies in the United States and Canada},
  author = {Lu, Haidong and Cole, Stephen R. and Westreich, Daniel and Hudgens, Michael G. and Adimora, Adaora A. and Althoff, Keri N. and others},
  journal = {Clinical Infectious Diseases},
  volume = {73},
  number = {7},
  pages = {e1408--e1414},
  year = {2021},
}