Our research in privacy and security takes an interdisciplinary approach to detecting and removing threats of cyberattacks, enhancing predictability and trust, and understanding online privacy and information manipulation. Our research methodology is rooted in several disciplines, including computer science, applied mathematics, cognitive science, control theory, economics, social sciences, and public policy. Specifically, we conduct research to understand issues and seize opportunities in systems and software security, usability considerations in privacy and security, economics of information security, and data-driven security, among many others.

Assistant Professor
Machine Learning; Adversarial Machine Learning; Security and Privacy in Machine Learning

Associate Teaching Professor
Cybersecurity Education; Cybersecurity; Situation Awareness

David Reese Professor of Information Sciences and Technology
Machine and Deep Learning; Artificial Intelligence; Text Processing and Knowledge Extraction

Assistant Professor
Robotic Vehicle Security; Software Security; Embedded Systems Security

Assistant Professor
Artificial Intelligence and Machine Learning; Cyber-Physical Systems and Smart & Connected Communities; Cybersecurity

Raymond G. Tronzo, MD Professor of Cybersecurity
Computer Security; Building Secure Software Systems; Secure Internet of Things

Assistant Research Professor
Biomedical Informatics; Data Privacy; Applied Statistics

Assistant Professor
Machine Learning and AI; Privacy and Security; Replication and Confidence in Science

Frymoyer Chair in Information Sciences and Technology
Privacy; Access Control; Online Deviance

Assistant Professor
Natural Language Processing; Privacy; Computational Social Science

Assistant Professor
Human Factors; Cybersecurity and Privacy; Human Perception and Action

Assistant Professor
Responsible Artificial Intelligence; Social Network Analysis; Machine Learning