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
Assistant Teaching Professor
Cybersecurity; Situation Awareness; Security Metrics
David Reese Professor of Information Sciences and Technology
Machine and Deep Learning; Artificial Intelligence; Text Processing and Knowledge Extraction
Assistant Professor
Artificial Intelligence; Multiagent Systems; Game Theory & Mechanism Design
Assistant Professor
Robotic Vehicle Security; Software Security; Embedded Systems Security
Raymond G. Tronzo, MD Professor of Cybersecurity
Computer Security; Building Secure Software Systems; Secure Internet of Things
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
Professor
Artificial Intelligence; Multiagent Systems; Knowledge Representation and Reasoning