The continued growth of interdisciplinary scientific research as well as the advent of big data has been a hallmark of the past few decades. It is increasingly important to be able to connect disciplines in order to further scientific knowledge. As an applied biostatistician, my work is based squarely within the mathematical sciences, but spans other fields in order to ensure that research is conducted on a sound footing. The real-world research problems that these investigators face often require the use of novel solutions and approaches, since existing methodology is sometimes inadequate. Bridging the gap between theory and practice in interdisciplinary settings is often a challenge, and has been a particular focus of my work.
My statistical methodological research continues to focus on the development of approaches to account for multivariate response models, longitudinal studies and missing data. I recently completed a fellowship through the ASA/NSF/Bureau of Labor Statistics program, where I led a project to improve imputation methods for the Occupational Employment Survey.
In addition to developing new methods, there is a pressing need for statisticians to help disseminate and promulgate the use of modern approaches, as well as to to help ensure that scientific investigations are conducted on a solid statistical footing. Many of these projects have involved undergraduate students. I welcome these opportunities to help introduce students to research and consider this a key part of my teaching and scholarship.