Rate My Professor Yu Cheng

Her research specializes in dynamic treatment regimes, sequential multiple assignment randomized trials (SMART) and adaptive designs, causal inference, win statistics for multiple endpoints, complex clinical trial designs, disease classification, risk evaluation, quantile association, competing risks regression and association analyses, and discriminant analysis. Applications include collaborative projects on COVID-19, HIV, smoking cessation, systemic lupus erythematosus, bipolar disorder, depression, eating disorders, and cystic fibrosis. Cheng is a Fellow of the American Statistical Association, elected in 2024, and recipient of the ASA Pittsburgh Chapter Statistician of the Year award in 2020. She has held leadership roles such as President of the ASA Pittsburgh Chapter from 2014 to 2015 and Treasurer of the ASA Lifetime Data Science Section from 2021 to 2023. As Associate Editor for Lifetime Data Analysis since 2021 and Journal of Statistical Research since 2015, she contributes to the field editorially. Key publications include Yang, X., Cheng, Y., Thall, P., Wahed, A. (2024) “A generalized outcome-adaptive sequential multiple assignment randomized trial design,” Biometrics; Lyu, L., Cheng, Y., Wahed, A. (2023) “Imputation-Based Q-Learning for Optimizing Dynamic Treatment Regimes with Right-Censored Survival Outcome,” Biometrics; Wang, Z., Cheng, Y., Seaberg, E.C., Becker, J.T. (2022) “Quantifying Diagnostic Accuracy Improvement of New Biomarkers for Competing Risk Outcomes,” Biostatistics; Li, R., Cheng, Y., Fine, J. (2014) “Quantile association regression models,” Journal of the American Statistical Association. Her work influences statistical methodology for personalized medicine and clinical trials.