The Ph.D. in Analytics and Data Science is an advanced degree with a dual focus of application and research - where students will engage in real world business problems, which will inform and guide their research interests.

To ensure that our Ph.D. students in Analytics and Data Science are exposed to the latest issues and challenges of working across a wide variety of data contexts, individuals will be required to engage with one (or more) of the dozens of organizations which have agreed to sponsor doctorate-level projects for a minimum of three semesters (9 credit hours of engagement + 15 credit hours of dissertation research). These organizations span the continuum of application domains, including health care, banking, retail, government, and consumer finance. Students will also continue to work with the faculty adviser through their final year of project engagement and dissertation research.

The materials in this collection consists of research conducted by PhD candidates as a means to showcase the important work being done in the program.

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Submissions from 2022


Directional Pairwise Class Confusion Bias and Its Mitigation, Sudhashree Sayenju, Ramazan Aygun PhD, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang PhD, Bill Franks, Sereres Johnston PhD, George Lee, Dan Sullivan, and Girish Modgil PhD

Submissions from 2019


Evaluating the Impact of Proactive Care Management with IDStrat, D.J. Donahue and Lauren Staples


Outcome Prediction in Intensive Care Unit Settings with Claims Data, Lauren Staples and Ryan Rimby


A Product Affinity Segmentation Framework, Lili Zhang, Jennifer Priestley, Joseph DeMaio, and Sherry Ni


A Descriptive Study of Variable Discretization and Cost-Sensitive Logistic Regression on Imbalanced Credit Data, Lili Zhang, Jennifer Priestley, Herman Ray, and Soon Tan