Hongxiang (David) Qiu, PhD

I am interested in a variety of problems in causal inference, missing data, prediction sets, and machine learning. My goal is to make the most of all the available data and scientific knowledge to obtain valid conclusions without introducing extra assumptions that might make the results of my methods unreliable. To do this, I often work with semiparametric or nonparametric statistical models and leverage machine learning techniques to maximize the chances of obtaining valid inferences. I am also working on several projects on perinatal & pediatric epidemiology. I have also worked on a cluster-randomized trial (PROUD trial), contributing to the statistical analysis plan, the algorithm defining the primary outcome based on electronic health records, data quality checking, and statistical analyses

PUBLICATIONS

• https://www.degruyter.com/document/doi/10.1515/em-2024-0008/html 
• https://projecteuclid.org/journals/annals-of-statistics/volume-52/issue-4/Efficient-and-multiply-robust-risk-estimation-under-general-forms-of/10.1214/24-AOS2422.full
• https://academic.oup.com/jrsssb/advance-article/doi/10.1093/jrsssb/qkad069/7225361
• https://www.degruyter.com/document/doi/10.1515/jci-2022-0005/html
• https://www.tandfonline.com/doi/abs/10.1080/01621459.2020.1745814
• https://arxiv.org/abs/2209.04364
• https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-020-4148-z