About me

I'm an Assistant Professor in the Department of Environmental Health and Engineering at Johns Hopkins University. My research involves policy-relevant issues at the intersection of AI/data science, environmental justice, and health equity. Recent areas of focus include planetary health, humanitarian operations, and climate adaptation. I completed my PhD in Biomedical Data Science at Stanford and obtained a BS in Statistics at the University of Chicago. I've also worked in data science roles for the World Health Organization and Médecins Sans Frontières.

If you are a prospective PhD student interested in working with me, consider applying to Hopkins EHE through the track on Environmental Sustainability, Resilience, and Health and mentioning my name in your application. For potential postdocs or students already at Hopkins, please ping via email.

Feel free to reach out if you'd like to discuss any shared interests or potential collaborations. My email is bhuynh {at} jhu {dot} edu. My last name can approximately be pronounced "hwin" or "win," and my pronouns are he/him.

Selected publications

For a full list of publications, see here: Google Scholar.

Estimated Childhood Lead Exposure From Drinking Water in Chicago
JAMA Pediatrics, 2024
Huynh BQ, Chin ET, & Kiang MV. [The Guardian] [The Washington Post] [CNN] [NPR] [Chicago Sun-Times] [CBS] [NBC] [ABC] [Show abstract]

Mitigating allocative tradeoffs and harms in an environmental justice data tool
Nature Machine Intelligence, 2024
Huynh BQ*, Chin ET*, Koenecke A, Ouyang D, Ho DE, Kiang MV, & Rehkopf DH. *Co-first author. [arXiv] [Grist, SF Chronicle, SFGate, Long Beach Post, Jefferson Public Radio, and more via CalMatters] [Show abstract]

AI for Anticipatory Action: Moving Beyond Climate Forecasting
Proceedings of the 2023 AAAI Fall Symposia
Huynh BQ & Kiang MV. [Show abstract]

Public health impacts of an imminent Red Sea oil spill
Nature Sustainability, 2021
Huynh BQ, Kwong LH, Kiang MV, Chin ET, Mohareb AM, Jumaan AO, Basu S, Geldsetzer P, Karaki FM, & Rehkopf DH. [Invited commentary] [Nature research highlight] [Stanford press release] [BBC] [CNN] [The Economist] [The Guardian] [Al Jazeera] [The New Yorker] [The World] Update: disaster averted! [Show abstract]

Routine asymptomatic testing strategies for airline travel during the COVID-19 pandemic: a simulation analysis
The Lancet Infectious Diseases, 2021
Kiang MV, Chin ET, Huynh BQ, Chapman LAC, Rodríguez-Barraquer I, Greenhouse B, Rutherford G, Bibbins-Domingo K, Havlir D, Basu S, & Lo NC. (Editor's choice.) [UCSF press release] [NPR] [ABC News] [SF Chronicle] [Cited in CDC report] [Cited in UK guidance] [Show abstract]

Frequency of routine testing for COVID-19 in high-risk environments to reduce workplace outbreaks
Clinical Infectious Diseases, 2020
Chin ET*, Huynh BQ*, Chapman LAC, Murrill M, Basu S, & Lo NC. *Co-first author. [Cited in CDC guidance] [Cited in Africa CDC Guidance] [Cited in UC System-wide testing recommendations] [Show abstract]

Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study
BMC Medicine, 2020
Chin ET*, Huynh BQ*, Lo NC, Hastie T, & Basu S. *Co-first author. [Cited in WHO report] [Show abstract]

Forecasting internally displaced population migration patterns in Syria and Yemen
Disaster Medicine and Public Health Preparedness, 2019
Huynh BQ & Basu, S. [Pre-print PDF] [Cited in UN report] [Show abstract]

A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets
Medical Physics, 2017
Antropova NO*, Huynh BQ*, & Giger ML. *Co-first author. (Editor's choice.) [Show abstract]

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks
Journal of Medical Imaging, 2016
Huynh BQ, Li H, & Giger ML. [Show abstract]