PhD Epidemiology Alumni

I received my PhD degree in epidemiology under the supervision of Dr. Claudia Holzman at Michigan State University in December 2016. Currently, I am a Research Assistant Professor in the Clinical and Translational Sciences Institute (CTSI) at MSU. My current research interest is to identify various omics-based biomarkers in human body fluids (e.g., blood, urine, etc.) and/or tissues that effectively predict the risk/pathogenesis/prognosis of human disease(s) or classify disease phenotypes for precise treatment in clinical settings and/or epidemiological context by using an integrative approach that combines knowledge and skills in multiple disciplines including epidemiology, biostatistics, bioinformatics, molecular biology and biochemistry, and clinical medicine. Since 2017, I have been involved in completing a total of 14 research papers with 8 published and 6 submitted. Recently, as a PI, I developed an NIH R01 grant proposal regarding the pathway-based microRNA signatures in maternal plasma in relation to spontaneous preterm birth, which will be re-submitted to the NIH in this November. Meanwhile, I’m also invited to join a collaborative R01 project as a co-investigator responsible for the bioinformatics analysis of the single-cell RNA sequence data derived from pancreatic cancer. In addition, I am currently an active reviewer for some peer-reviewed journals such as American Journal of Epidemiology, BJOG, PLoS ONE, BMC Medical Genomics, and Current Pediatric Reviews.

Reflecting on my training in the epidemiology PhD program at MSU and my current independent research, I feel that at least four skills – integration, critical thinking, independence, and collaboration that I learned from this outstanding program are critical for my academic career development. These four “latent” skills can be trained via studying the core and elective courses that the department offers, for instance, the balanced set of both biostatistics and epidemiology courses, the course for writing epidemiologic research grants, the required independent study credit, the assigned individual and group research projects in each of the epidemiology courses, and the final dissertation studies with the committee members. Along with these four critical skills, the specific knowledge and skills in both epidemiology and biostatistics from this program also significantly boosted my self-confidence to continuously step outside my comfort zone in research. As a consequence, I’ve recently started applying Python and R machine learning algorithms into the identification of various omics-based biomarker signatures from human body fluids and/or tissues in relation to human chronic diseases in the clinical settings or the epidemiological context.