Sara Burns, winner of the John J. Bartko Scholarship; Jami Jackson Mulgrave, winner of the Lester R. Curtin Award; and Jinyuan Liu, winner of the Lingzi Lu Memorial Award, will receive registration and travel support to attend the ASA Conference on Statistical Practice.
John Bartko Scholarship
John Bartko scholarship winner Sara Burns earned a master’s in biostatistics from Washington University in St. Louis in 2016. She is now employed by the Department of Anesthesia, Critical Care, and Pain Medicine at Massachusetts General Hospital. Her projects range from designing randomized controlled trials for new medical devices to analyzing data from objective studies that aim to reduce pain medicine prescriptions in light of the current opioid epidemic.
Burns is looking forward to attending lectures and taking a course at CSP to strengthen her R coding skills. She ultimately strives to become an expert in applying statistical techniques to answer meaningful questions in the medical field. She is passionate about improving the quality of research published in scientific articles, on which doctors base their clinical practice.
Lester Curtin Award
Jami Jackson Mulgrave earned a bachelor’s degree in psychology from Columbia University and a master’s degree in statistics (concentration in statistical genetics) from North Carolina State University. She is working toward a PhD, doing research on Bayesian nonparametric methods for graphical models of genetic data. She has a large set of programming and data visualization skills. Additionally, Mulgrave is involved in numerous student activities. She has been the NCSU chapter president of SACNAS and served as a science communicator for the North Carolina Museum of Natural Sciences. She is also involved in a program to introduce the STEM fields to sixth- to eighth-grade students from under-represented populations. Her long-term goal is to be a professor of biostatistics.
Lingzi Lu Memorial Award
Jinyuan Liu earned an MA from the department of biostatistics and computational biology at the University of Rochester. She is currently employed as a research assistant in the VA San Diego Healthcare System in California, where she is working on two methodological projects on causal inference and social network data analysis and their applications to drug surveillance and depression. She is also working on several collaborative projects, including meta-analysis, variable selection, and intra-class correlation. Her ultimate career goal is to develop new statistical models and conduct statistical inference in complex studies in an academic environment to help improve the understanding of human illness and health.