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The Center is pleased to showcase just a few of the projects completed by teams comprised of faculty from diverse fields from across campus that are transforming data analytics and statistical methods into insight and solutions locally and abroad.

Dr. Maria Weese, Dr. Waldyn Martinez, and Dr. Allison Jones-Farmer are working to improve methods to monitor complex, dynamic processes that produce many data streams in order to more quickly detect unusual events. In areas such as public health, information security, and social media, multiple, correlated data streams can be modeled simultaneously to detect unusual events such as a disease outbreaks, network intrusions, or a public relations crises.

Accuracy, timeliness, consistency, and completeness of the data are critical, and Jones-Farmer's work explores how an organization can monitor the quality of the data to improve the data quality and ultimately the quality of the decisions based on the data.

With a dedication to sustainability and business practices, much of Dr. Robert Dahlstrom's research examines the intersections of business management and the environment.

Recently, Dahlstrom and his collaborators Jakob Utgaard and Arne Nygaard at the BI Norwegian School of Business have used data from a large set of experimental observations to pinpoint major variables that impact underage alcohol purchases in Norway.

Dr. Byran Smucker and his collaborators, graduate student Xinping Zhang and Jay Woffington, executive director of the Cincinnati Shakespeare Company, have created a new predictive analytics tool to help effectively examine business performance. Specifically, the application was created to allow the theater to predict, several weeks before a show opens, whether sales for the show will exceed or fail to meet institutional targets.

Dr. Amélie Davis began research in bee habitat conservation in 2011. She and collaborators have developed a modeling tool to analyze large sets of spatial data. The model helps show how different spatial arrangements of types of crops and natural areas across the US impact the health of honeybee populations. Using massive amounts of satellite data, the model helps answer what areas are the most effective spaces to conserve in order to protect wild and honey bee populations.