Welcome to my site. I am a Quantitative Psychology Ph.D. student in the Department of Psychology and Neuroscience, a Mathematical Statistics M.S. student in the Department of Statistics and Operations Research, at UNC Chapel Hill. I am also a graduate student member of the L. L. Thurstone Psychometric Laboratory under the Quantitative Psychology Graduate Program, and a Research Assistant at Yun Li Statistical Generics Group under the Department of Genetics, UNC School of Medicine.
My primary research aims to resolve the methodological and modeling issues that commonly arise in psychology applications. When searching for effective ways of unpacking psychological data that helps understand underlying mechanisms, two general themes surround this overarching goal: 1) the measurement of unobserved (aka. latent) variables, and 2) the modeling of the developmental processes. The statistical modeling technique that I use to tackle these themes is the latent variable modeling (LVM) or structural equation modeling (SEM) and their longitudinal extensions such as panel models, hidden Markov models, and time series. These models are related to and often be compared with many framework including but not limited to finite mixture models, multilevel models, network psychometric models. Specifically, my work focuses on the statistical computing and programming to advancing the estimation procedure of these models, as well as the casual versus associational interpretations of the results based on model assumptions.
For example, recently I have been working in Gate’s lab on methods development and interpretations of individual dynamic models using intensive longitudinal data (ILD) or time series data that is typical in daily dairy or functional magnetic resonance imaging (fMRI) studies. This type of research focuses on within-person variabilities and modeling the heterogeneous nature of each individual from an idiographic approach, as compared to the nomothetic approach that emphasized making inferences to the general population based on between-person variabilities. My work aims to evaluate two frameworks to estimate these individual models, that is, the traditional SEM extended for ILD (i.e., united SEM) versus the recently developed network psychometric models, in terms of the analytical efficiency, causal interpretation, as well as the treatment of heterogeneity in individual dynamics and the adoption of group-level information in the process. A special contribution to intensive longitudinal SEM in general is that we adopt statistical learning methods to improve the performance of model selection regimes and estimation algorithms in SEMs. See here for the OSF site of our recent paper.
Secondarily, I have a substantive line of research that involves applications in varying contexts including but not limited to educational and psychological science, social and behavioral, clinical and health practice, and more recently social epidemiological research. My substantive research is situated predominantly in establishing developmental theories and dealing with questions such as identifying indicators of underlying developmental processes in personal traits, health outcome or chronical diseases. Particularly, I strive to understand and disentangle themes such as within-person versus between-person processes of stability and change, inter-individual difference in the intra-individual variations of these functions, or time-specific and person-specific components of change. Questions follows under these realm is both theoretically and practically important, because the understanding of how individuals differ or develop at different life stages can help people reach their full potential or prevent the onset of a rare decease. See here for a link to an example paper in education.
Beyond academic research, I have been involved in industrial applications through summer and long-term internships. For more information, see Industry Employment page or download my CV from the Curriculum Vitae page.
“The many, as we say, are seen but not known, and the ideas are known but not seen” (Plato, The Republic)