A person walking quietly through a park might never be heard by others, but if a flock of birds flies away as the person passes it is revealed that someone is there. Technology capable of discovering quiet agents in real-time, using machines to analyze environments, could prove immensely useful.

MSDS students Boh Young Suh, JB Park and James Xie worked with Prof. Quanquan Gu to develop a spatial model to find the intersections across Virginia with the most deadly crashes.

MSDS 2018 Cohort students Kia Duan, Nitesh Prakash, Duncan Rule and Ni Zhuang worked to create a program that could more accurately assess threat levels from rallies and protests led by extremist groups.

Using machine learning to understand the adversary in credit card fraud

MSDS students Morgan Wall, Ali Zaidi and Dreisbach are exploring how immune system cells can be used to address neurological injuries and disorders.

According to the Center for Disease Control, over 38,000 US adults die annually due to liver disease.

MSDS students Gregory Wert, Elaine Liu and Greenawald, along with faculty advisor Don Brown, are undertaking a capstone research project sponsored by the U.S. Army Research Laboratory to provide that system, with language at its core.

The ability to sift through massive amounts of unstructured text data in a meaningful and impactful way can yield tremendous value towards businesses across a multitude of domains.

Using a data visualization process to translate research in a clear, practical way for broad audiences

Developing a database to help analysts store and process requests for intelligence