This workshop is a concluding event to an Undergraduate Summer Institute on "Big Data, Human Health and Statistics" held at the Department of Biostatistics, University of Michigan, Ann Arbor from June 1-26 and is intended to be an event focusing on the undergraduates. The training of the next generation of quantitative scientists needs to change to meet the demands of the data. We define "Big Data" as datasets of enormous size and complexity (either in number of observations, and/or in the number/nature of predictors/outcomes). Classical theory, computation and intuition often fail for such irregular, sparse data sets of vast size. More training in data management, data storage, visualization, high dimensional statistics, optimization, causal methods, modeling sparse data, machine learning are needed to equip students to tackle these big data challenges. It is expected that the knowledge obtained from these massive heterogeneous data sources will inform prevention, screening, prognosis, and treatment of human diseases and play a major role in biology, medicine, and public health in the coming decade. This workshop lies in the intersection of Big Data, Human Health and Statistics.
In this two-day symposium, the first day will feature talks by distinguished researchers in areas of relevance to Big Data, including mobile health, precision medicine, genomics, data visualization. There will be a poster session by undergraduate attendees and an oral presentation session by the undergraduate participants of the summer institute. The second day will be a professional development workshop for undergraduate attendees. Registration will be open to anyone interested (with a maximum limit of 120 participants). The grant will support participation cost of selected undergraduate attendees, faculty mentors and outside speakers.
