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Monthly Faculty Spotlight - April 2025

Q&A with Dr. Hongmei Zhang, PhD, MS

Professor of Biostatistics, EBE Division Director

1. What brought you to the U of M School of Public Health? 
   I was attracted to the UofM School of Public Health by its high potential and energy. It has been 11 years since my arrival and I have been impressed every moment by its growing as an R1 University.
   
   
2. What is the broad focus of your research? 
   My research focus is on two directions, generally speaking, collaborative research on allergic diseases and related, and biostatistical methodology research on clustering and network constructions/comparisons with application to population health data including phenotypic and genetic/epigenetic data.
   
   
3. What inspired you to pursue this particular area of research? 
   My interest in this area started from an informal discussion on asthma related studies in a hallway with my colleague more than 15 years ago. The vast unknowns, convolution in this area and the impact of the disease to people鈥檚 quality of life motivated my first collaborative project with them. Since then, I have been enjoying every single project in this area. In addition, those projects have been so inspiring to my methodological work, and I must say that most of my methodology work was motivated by collaborative projects.
   
   
4. What is the most exciting project you are currently working on? 
   Currently, we are working on a set of projects funded by the National Institute of Allergy and Infectious Diseases in the National Institutes of Health. One of the projects focuses on developing and applying a network-based clustering approach to detect joint epigenetic markers at birth associated with the risk of asthma incidence later in life. Findings from this project will have a potential to predict the risk of asthma at a much earlier age before disease manifestation and such a potential is extremely exciting.
   
   
5. How does your research impact or benefit the broader community or public health field? And how do you envision your research evolving in the next few years? 
   I truly enjoyed the projects that I have done and am doing. Findings from the applied projects improved people鈥檚 understanding to the underlying mechanisms of certain health conditions such as asthma, and the detected markers have a potential to predict disease manifestation at a much earlier age. Methodologically, I am confident that our developed innovative biostatistical methods have established new methodological research areas, potentially beneficial to all statisticians or biostatisticians.
   
   
6. What is the coolest training or program you've been a part of, or your favorite conference you've attended? 
   So far, the most enjoyable conferences include the annual Joint Statistical Meeting (JSM) for all statisticians and data scientists, and the annual conference organized by the American Academy of Allergy, Asthma, and Immunology (AAAAI). Through JSM, I will be able to stay informed about current progress in my research field and identify new research areas. The AAAAI conference is the best place for me to meet my domestic and international collaborators and identify new collaborative projects or research proposals.
   
   
7. What is your favorite self-authored manuscript? 
   I like the book that I published in 2020, Analyzing High Dimensional Gene Expression and DNA Methylation Data with R (Chapman & Hall). It is a platform for me to share with readers what I learned and have achieved in the past more than 10 years when working with genetic and epigenetic data. The manuscript that I liked the most is a 鈥渉istorical鈥� article led by my post-doctoral fellow, Dr. Shengtong Han, and published back in 2015, 9(4), 2052-2072, Annals of Applied Statistics. This article established a foundation for subsequent methodological work in the field of clustering and network constructions and comparisons.
   
   
8. What kind of research would you like to be doing that you haven't yet had the opportunity to do? 
   I really want to identify time to step into the bulging field of large language modeling. It is great to see that the EBE Division has faculty who already have started their research in this area, e.g., Drs. Xichen Mou and Yu (Joyce) Jiang. I am confident that they will be among the leaders in this field.
   
   
9. Are there any publications, awards, or recognitions you would like us to include in the spotlight? 
   I think you can mention that I was elected in 2021 as a Fellow of the American Statistical Association, one of the highest honors to statisticians.