This award supports participation in the workshop "Statistical Inference for Biomedical Big Data: Theory, Methods, and Tools" to be held on the Gainesville campus of the University of Florida, Gainesville, Florida on April 7-8, 2017. Dramatic improvements in data collection and acquisition technologies in the past two decades have enabled scientists to collect vast amounts of health-related data in biomedical studies. If analyzed properly, these data can expand our knowledge and improve contemporary healthcare services from diagnosis to prevention to personalized treatment, and can also provide insights into reducing healthcare costs. However, biomedical data can be rather big and complex, and are often characterized by some mixture of high dimensionality, heterogeneity, high volume, high velocity, and high variety. Advances in biomedical big data analysis can greatly impact the development of biomedical sciences.
This workshop will bring together some of the most prominent statisticians in biomedical big data and a selected group of local biomedical researchers in a collaborative setting to discuss and foster cutting-edge developments of statistical theory, methods, and tools for biomedical big data analysis. The format of this workshop is designed to foster interactions between statisticians and biomedical researchers. To facilitate communications between graduate students, junior researchers, and senior researchers, a poster session is included in the program. To disseminate the results of the meeting, the program and abstracts will be widely circulated, and modest travel funds for a large geographically diverse group of graduate students, postdocs, and junior faculty are planned. More information about the workshop can be found at http://biostat.ufl.edu/seminars/biostatistics-workshop/.
