Donglin Zeng

PhD, School of Public Health, UNC-Chapel Hill, Clinical Research

Donglin Zeng

School of Public Health
UNC-Chapel Hill
Clinical Research

3103-B Mcgavran-Greenberg Hl

Area of interest

I am currently serving as the co-director of Survey Sampling Unit in Department of Biostatistics. My research in this area is to study different sampling design (RDD, cellphone, response dependent sampling and multi-frame and complex sampling), help collect data from sampled respondent, and develop innovative statistical methods to handle sampling issue and obtain accurate estimates. Survey sampling is a commonly used approach for collecting data in cancer genetics and epidemiology, especially when interest focuses on studying cancer-related problems in some particular population, even hard-to-reach subjects.
My methodological research primarily focuses on semiparametric models and highdimensional data arising from a variety of statistical or biostatistical areas, including cancer survival or relapse time data analysis, longitudinal biomarker analysis, clinical trials, high-dimensional genetic data, and medical diagnostics. In the past ten years, I have published extensively in leading statistical journals. My work has been
internationally recognized and I have been invited to present his research all over the world. I have served as co-investigator on multiple NIH grants. Particularly, my research contribution to semiparametric models and inference mainly lies in extensive work on developing transformation models for the analysis of various types of censored data which largely exist in cancer-related events (death and relapse). Particularly, I
proposed general transformation models for modeling counting processes, clustered survival data, recurrent events, cured survival, and joint analysis of recurrent events and terminal event. My other research area lies in developing correct and efficient inference for emerging applications. Particularly, he and his co-author(s) developed an efficient
likelihood approach for analyzing haplotype-environment interactions with uncensored or censored outcomes and under cohort or case-control designs in a discussion paper.
We further considered haplotypes analysis in nested case-control or case-cohort study. We also developed a correct approach for handling second phenotype in a biased sample design and showed the equivalence between meta-analysis and mega-analysis in genome-wide association. Some of my recent work also studies reinforcement learning
in non-small cell lung cancer trial and disease surveillance. In addition to methodology development, my research also includes developing sample size/power calculation for case-cohort studies with rare and non-rare disease, developing efficient computing algorithms for transformation models, and developing efficient sampling approaches for
non-smooth estimation .
In the past years, I have collaborated extensively with investigators from various areas of disease including cancer, breast imaging, radiology, HIV, and genetic epidemiology within UNC or outside UNC. My successful collaborations have led to 27 articles published in medical journals such as AIDS, Radiology, Academic Radiology, American Journal of Neuroradiology, and JAMA.

Awards and Honors

1993 Guo-Moruo Award, The University of Science and Technology of China
1997 Qualify Exam Excellence Award, Dept. of Statistics, The University of Michigan
2001 Travel Award, Rackham Graduate School, The University of Michigan
2002 Center for AIDS Research Development Award, The University of North Carolina
2006 Junior Faculty Development Award, The University of North Carolina
2008 Noether Young Scholar Award, American Statistical Association
2008 Roy Kuebler Fund Award, Department of Biostatistics, The University of North Carolina
2010 Elected IMS Fellow
2011 Elected ASA Fellow

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