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Ruopeng An

Ruopeng An conducts research to assess population-level policies, local food and built environment, and socioeconomic determinants that affect individuals’ dietary behavior, physical activity, sedentary lifestyle, and adiposity in children, adults of all ages, and people with disabilities. His research aims to develop a well-rounded knowledge base and policy recommendations that can inform decision-making and the allocation of resources to combat obesity.

An’s research has been funded by federal agencies and public/private organizations (e.g., OpenAI, Abbott, Amgen). He has wide teaching and methodological expertise, including applied artificial intelligence (machine and deep learning), quantitative policy analysis (causal inference, cost-benefit and cost-effectiveness analysis, and microsimulation), applied econometrics and regression analysis, and systematic review and meta-analysis. He founded and chairs the Artificial Intelligence and Big Data Analytics for Public Health (AIBDA) Certificate program and hosts the “Artificial Intelligence in the Social Sciences” Open Classroom series. He has repeatedly been recognized for teaching excellence, receiving student evaluations in the top 10% of University faculty.

With over 200 peer-reviewed journal publications, Dr. An is recognized as one of Elsevier’s top 2% most cited scientists. His work has been highlighted by media outlets such as TIME, New York Times, Los Angeles Times, Washington Post, Reuters, USA Today, Bloomberg, Forbes, Atlantic, Guardian, FOX, NPR, and CNN. He serves on research grants and expert panels for NIH, CDC, NSF, HHS, USDA, and the French National Research Agency. He is a Fellow of the American College of Epidemiology.

Ruopeng An

Areas of Focus:

  • Applications of artificial intelligence, machine/deep learning, and big data analytics in public health
  • Environmental and policy influences on dietary behavior, physical activity, and obesity
  • Social and economic determinants of health

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