Rate My Professor Rui Duan

Rui Duan is an Associate Professor of Biostatistics at the Harvard T.H. Chan School of Public Health, where she also serves as a primary faculty member in the Department of Epidemiology and is affiliated with the Harvard Data Science Initiative. She joined the faculty as an Assistant Professor in July 2020 following the completion of her Ph.D. in Biostatistics from the University of Pennsylvania in 2020. Prior to her doctoral studies, she earned an M.S. in Biostatistics from Duke University in 2015 and a B.S. in Mathematics from Fudan University in 2013. Duan was promoted to Associate Professor of Biostatistics in 2025. Her research centers on developing statistical and machine learning methods for biomedical data integration and analysis. Key areas include predictive modeling for disease risk using electronic health records and biobanks, detection of cross-phenotype associations and pleiotropy in high-dimensional data, federated learning, meta-analysis for evidence synthesis, and methods to handle suboptimality in real-world data such as missing data and measurement errors. These efforts aim to support precise diagnostics, individualized treatments, and improved patient outcomes. Her work is supported by funding from the National Institutes of Health, Harvard Chan School of Public Health Dean's Fund for Scientific Achievements, Harvard Data Science Initiative Competitive Research Fund, and Google Research Scholar Award.

Duan has received numerous prestigious awards and honors recognizing her contributions to biostatistics and informatics, including the Saul Winegrad Award for Outstanding Dissertation, IMS New Researcher Travel Award, 2018 Best Paper Award by the International Medical Informatics Association Yearbook Section on Clinical Research Informatics (selected as one of the top five papers from 741 submissions), Jiann-Ping Hsu Pharmaceutical and Regulatory Sciences Student Paper Award (first place, International Chinese Statistical Association Student Paper Award), Eastern North American Region Distinguished Paper Award (2018), first place in the American Medical Informatics Association Knowledge Discovery and Data Mining Student Paper Competition (2016), and Jonathan Raz Award for Best Qualifying Examination (2016). Notable publications include 'Fast and robust invariant generalized linear models' (Journal of Computational and Graphical Statistics, 2025), 'Real-time dynamic polygenic prediction for streaming data' (Nature Genetics, 2025), 'Early detection of non-small cell lung cancer: an electronic health record data-driven approach' (BMC Medicine, 2025), and 'Genome-wide association studies in a large Korean cohort identify quantitative trait loci for 36 traits and illuminate their genetic architectures' (Nature Communications, 2025).