About
I am an associate Professor and former Graduate Program Director of Statistics, in the Department of Mathematics and Statistics of UMBC, and an affiliate faculty at Joint Doctoral Program in Gerontology, Department of Preventive Medicine and Epidemiology, School of Medicine, UMB. I took an extended sabbatical working at NIBIB as a 2023 NIH Data Scholar during 12/2023 - 12/2024, working on national Covid over the counter testing data. I joined UMBC in 2007 after completing my Ph.D in Biostatistics at Johns Hopkins University School of Public Health. I got a MS in Atmospheric Science at UCLA and BS at Peking University. As a biostatistician, I design studies and carry on data analysis for public health/ biomedical studies, as well as develop new statistical approaches to deal with complex study designs or new challenges in real data, especially propensity score based causal inference methods in treatment efficacy/ safety evaluation and Meta Analysis.Research interests
My passion for future research is to contribute the efficacy and safety assessment of innovative therapy (study design and analysis using causal inference techniques in both development stage and post-market stage) and important public health issues, in particular prevention science. My research has been focused on the applied statistical/ biostatistical methods for the determination of average associational and causal effects of treatment/exposure/intervention on adverse health outcomes. The methodology research focused on causal inference research extending standard propensity score approaches to allow covariate measurement error, data synthesis methods (e.g. advanced meta-analysis for rare events, causal meta-analysis to synthesis treatment heterogeneity across RCT trials), treatment effect efficacy and safety assessment in causal framework. Current projects include FDA project - synthetic arm construction using propensity score integrated Bayesian leverage methods, cardiovascular and renal project using CARDIA study, gerontology projects with School of Medicine/ UMB, meta-analysis to synthesis treatment heterogeneity across trails, post-marketing safety studies of diabetes II drugs, advanced longitudinal method for binary recurrent event data, and up-to-date meta-analysis methodology dealing with rare binary outcome.Teaching interests
I love teaching. The classrooms and students have the magic power in energizing me regardless I teach in daytime or night time. Primarily, I teach biostatistics courses. For undergraduate students, I teach STAT 350 - Introduction to Statistics for Biology and Life sciences related majors, which is a large audience undergraduate course which I offers every semester. For graduate students, I teach STAT619 - Biostatistics Principle and Design where I teach causal inference, randomized clinical trials, and other observational studies, as well as STAT 603 -Categorical Data Anlaysis for graduate students in statistics major. I have advised quite a few Ph.D. and M.S. students through thesis research and independent studies (STAT 899, 898, and 699) since 2008. A few years ago, I also taught longitudinal data analysis and other graduate level statistics courses.Due to the dramatic swift to online teaching during pandemic time, I have fun learning new online tools and adopting more pedagogy techniques for becoming a better teacher online and in person. So, I completed two year training program with UMBC Faculty Development Center, the Active Learning, Inquiry Teaching (ALIT) certificate program during 2020 to 2022, and continued taking training seminars offered by faculty development centers and IT department of UMBC.
Education
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Ph D, Biostatistics
— Johns Hopkins University, Bloomberg School of Public Health (2007) Statistical Methods for the Determination of Average Associational and Causal Effects.
- MS, Atmospheric Science — University of California, Los Angeles (2000)
- BS, Atmospheric Physics — Peking University (1997)