Ruopeng An
Constance and Martin Silver Endowed Professor in Data Science and Prevention; Director, Constance and Martin Silver Center on Data Science and Social Equity
PhD, MPP
Areas of Expertise: Environmental influences and population-level interventions on obesity, weight-related behaviors and outcomes across the life course; Social and economic determinants and policies affecting physical, mental, and cognitive health in children, adults of all ages, and individuals with disabilities; Applications of artificial intelligence and data analytics for public health and social equity; Using data and statistical research methods to evaluate the effects of policies; Systematic review and meta-analysis to identify and appraise existing research.
Biography
Dr. Ruopeng An is a leading expert in obesity epidemiology and policy evaluation, a noted interdisciplinary data scientist, and an internationally recognized scholar in applying artificial intelligence to address public health disparities and social inequities.
He currently holds the Constance and Martin Silver Endowed Professorship in Data Science and Prevention and serves as the Director of the Constance and Martin Silver Center on Data Science and Social Equity. Dr. An is also an elected Fellow of the American Academy of Health Behavior and the American College of Epidemiology.
His research has been funded by various federal agencies and public/private organizations, including OpenAI, Abbott, and Amgen. Recognized as one of Elsevier’s top 2% most cited scientists, his work has been featured by major media outlets such as TIME, The New York Times, The Los Angeles Times, The Washington Post, Reuters, USA Today, Bloomberg, Forbes, The Atlantic, The Guardian, FOX, NPR, and CNN. He also serves on research grants and expert panels for the NIH, CDC, NSF, HHS, USDA, and the French National Research Agency.
Before joining NYU, Dr. An was the Faculty Lead in Public Health Sciences and Faculty Fellow for AI Innovations in Education at Washington University in St. Louis, where he also founded two certificate programs focused on artificial intelligence and data science.
Dr. An holds a PhD in Policy Analysis from the Pardee RAND Graduate School, a Master of Public Policy from the National Graduate Institute for Policy Studies, and a BA in Political Science and Public Administration from Peking University.
Recent Publications
An, R., & Ji, M. (2023). Building Machine Learning Models to Correct Self-Reported Anthropometric Measures. Journal of Public Health Management and Practice, 29(5), 671-674.
An, R., Perez-Cruet, J., & Wang, J. (2024). We got nuts! use deep neural networks to classify images of common edible nuts. Nutrition and Health, 30(2), 301-307.
An, R., Perez-Cruet, J. M., Wang, X., & Yang, Y. (2024). Build Deep Neural Network Models to Detect Common Edible Nuts from Photos and Estimate Nutrient Portfolio. Nutrients, 16(9), 1294.
An, R., Yang, Y., Batcheller, Q., & Zhou, Q. (2023). Sentiment analysis of tweets on soda taxes. Journal of Public Health Management and Practice, 29(5), 633-639.
Yang, Y., Lin, N., Batcheller, Q., Zhou, Q., Anderson, J., & An, R. (2023). Sentiment Analysis of Tweets on Menu Labeling Regulations in the US. Nutrients, 15(19), 4269.
Huang, J., Guo, P., Zhang, S., Ji, M., & An, R. (2024). Use of Deep Neural Networks to Predict Obesity With Short Audio Recordings: Development and Usability Study. JMIR Artificial Intelligence, 3, e54885.
An, R., Batcheller, Q., Wang, J., & Yang, Y. (2023). Build neural network models to identify and correct news headlines exaggerating obesity-related scientific findings. Journal of Data and Information Science, 8(3), 88-97.
An, R., Byron Jr, C. W., Chen, C., & Xiang, X. (2023). A Field Test of Popular Chatbots’ Responses To Questions Concerning Negative Body Image. Health Behavior Research, 6(1), 3.
An, R., Yang, Y., Yang, F., & Wang, S. (2023). Use prompt to differentiate text generated by ChatGPT and humans. Machine Learning with Applications, 14, 100497.
An, R., Zheng, J., & Xiang, X. (2022). Projecting the influence of sugar-sweetened beverage warning labels and restaurant menu labeling regulations on energy intake, weight status, and health care expenditures in US adults: a microsimulation. Journal of the Academy of Nutrition and Dietetics, 122(2), 334-344.
An, R. (2020). Projecting the impact of COVID-19 pandemic on childhood obesity in the US: A microsimulation model. Journal of Sport and Health Science, 9(4): 302-312.
Tainio, M., Andersen, Z. J., Nieuwenhuijsen, M. J., Hu, L., De Nazelle, A., An, R., ... & de Sá, T. H. (2021). Air pollution, physical activity and health: A mapping review of the evidence. Environment international, 147, 105954.
An, R., Kang, H., Cao, L., & Xiang, X. (2022). Engagement in outdoor physical activity under ambient fine particulate matter pollution: A risk-benefit analysis. Journal of Sport and Health Science, 11(4), 537-544.
Si, Y., Yang, Y., Wang, X., An, R., Zu, J., Chen, X., ... & Gong, S. (2024). Quality and Accountability of Large Language Models (LLMs) in Healthcare in Low-and Middle-Income Countries (LMIC): A Simulated Patient Study using ChatGPT (No. 1472). GLO Discussion Paper.