Boosting customer retention for software-as-a-service companies with an XGBoost model

Using an adversarial learning approach to predict a fraudster’s next move

Studying real-time traffic data from the UVA network to test the performance of intrusion detection

Analyzing tweets from three metropolitan areas to study large temporal trends for a city as a whole

Applying performative analysis to predict linguistic rigidity in political, social and religious groups

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.