Machine Learning and Artificial Intelligence

Faculty and students in the School of Computing are engaged in fundamental and applied research projects focusing on machine learning, data mining, big data, artificial intelligence, and robotics.  Areas of research include anomaly detection, knowledge engineering, advanced pattern mining, graph mining and real-time reasoning.  These efforts have been successfully applied to various domains of social importance including public health, neurological disorders, highway safety, malware detection, autonomous robotic guides, social media, and molecular biology.

Research Groups:

Data Science Ensemble

Health Informatics

Faculty Members:

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Dr. David Bourrie Dr. David Bourrie
Associate Professor


Dr. Ryan Benton
CS Chair,
Associate Professor


Dr. Jingshan Huang Dr. Jingshan Huang


Dr. Tom Johnsten Dr. Tom Johnsten
CS Curriculum Coordinator


Dr. Aviv Segev Dr. Aviv Segev