My role as a statistician here, at the Center for Developmental Epidemiology (CDE), started on June 1993 after I finished a two-year visiting professorship at ISDS (Institute of Statistics and Decision Sciences) of Duke University. Prior to this assignment, I was a Ph.D. student at Carnegie Mellon University (CMU) Statistics Department, Pittsburgh, PA. I finished my degree in the summer of 1991 and came down south to start my first “real job” at ISDS. Already knowing a lot about Duke University’s commitment to quality research and teaching, I was thrilled to be offered such a great opportunity. I had two great years of experience at ISDS, and it paid off very well after I moved to my current post at CDE as an Assistant Research Professor.

         Being trained as a “hardcore” Bayesian (aka, “subjective”) statistician, courtesy of CMU Statistics Department, and also having strong background in Applied Mathematics, helped me to understand, and provide solutions for, the challenging problems our center encounters in a highly competitive grant-driven environment. My current major role for the CDE is to provide sophisticated methodology for combining information form several studies that are from different populations and sampling designs, for example the CCC, VTSABD, and GSMS. Some of my current research interests (included but not limited to) are the optimal design and analyses of multi-phase prevalence studies; markov regression models for longitudinal data; item-response modeling; and latent class analyses. As you may realize from my publication list, I endeavor (and, to some extend, enjoy) to create a balance between applications and methodology as they all feedback each other indefinitely. The highly sophisticated yet very relaxed environment at CDE provides an excellent research platform. In turn, CDE gains from my own research the necessary weapons to attack the complicated applied problems it endeavors.

    
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