I am an Assistant Member (Assistant Professor in Oncology) in the Department of Biostatistics and Bioinformatics at Roswell Park Comprehensive Cancer Center in Buffalo, NY, and hold secondary appointment as a Research Assistant Professor at University at Buffalo. I received my PhD in Epidemiology and Biostatistics from the School of Population and Public Health at the University of British Columbia.

My research is centered on developing innovative statistical methods to improve the design, analysis, and interpretation of clinical trials and public health interventions, with a particular emphasis on pragmatic trials, Bayesian adaptive designs, complex health data, and causal inference. My work aims to bridge statistical theory and real-world medical application by creating methods that are rigorous, interpretable, and responsive to the practical challenges encountered in clinical, epidemiologic, and public health research. Examples of my research agenda include: (1) improving the design and analysis of pragmatic clinical trials, particularly cluster randomized trials, by developing methods that address correlated outcomes, small numbers of clusters, complex implementation settings, and practical constraints in real-world intervention studies; (2) advancing Bayesian adaptive designs for early-phase and dose-finding trials, with the goal of enabling more efficient, flexible, and ethical learning from accumulating data; (3) developing statistical models and inferential tools for longitudinal and multilevel health data, especially in settings involving small sample sizes, hierarchical data structures, and complex correlation patterns; and (4) applying and extending quasi-experimental and causal inference methods, including interrupted time series and multiple baseline designs, to evaluate public health, policy, and health system interventions when randomization is infeasible. Across these areas, I am committed to developing methodological innovations that strengthen evidence generation and support meaningful real-world impact.

My research is strongly collaborative and is motivated by substantive problems in medicine, epidemiology, and public health. I work closely with clinicians, epidemiologists, public health practitioners, and other applied researchers to ensure that my methodological work is grounded in real scientific questions and can be translated into practical tools for study design, data analysis, and decision-making. Through these collaborations, my work contributes to evidence-based medicine, public health intervention evaluation, healthcare delivery research, and policy-relevant causal inference. A full list of my scholarly work can be found on my Google Scholar page.