Leadership
Lorrie Cranor
CO-FOUNDER AND CO-DIRECTOR,
Privacy Engineering Programs
Research Interests:
Usable privacy and security, Privacy decision making
Norman M. Sadeh
CO-FOUNDER AND CO-DIRECTOR,
Privacy Engineering Programs
Research Interests:
Mobile and pervasive computing, Cybersecurity, Online privacy, User-oriented machine learning, and Semantic web technologies with a particular focus on mobile and social networking
Hana Habib
Assoc. Director, Privacy Engineering ProgramS
Research Interests:
Privacy, privacy engineering, privacy policy and regulation, usability, usable privacy and security
Core Faculty
Alessandro Acquisti
Research Interests:
Economics and behavioral economics of privacy and information security, Privacy and security in online social networks, Economics of computers and AI, Agents economics, Computational economics, Ecommerce, Cryptography, Anonymity, Electronic voting
Yuvraj Agarwal
Research Interests:
Systems and Networking, Embedded Systems and Mobile Computing, Smart Buildings and Smart Grid, Energy Efficient and Resilient Computer Systems
Lujo Bauer
Research Interests:
usable security, proof-carrying authorization, distributed access control, program monitors, security automata, languages for specifying security policies
Travis Breaux
Research Interests:
Requirements and software engineering; Risk and legal compliance; Accessibility, privacy and security
Nicolas Christin
Research Interests:
Online crime modeling, usable and secure authentication and passwords, security economics
Jason Hong
Research Interests:
ubiquitous computing, especially mobile social computing and context-aware computing; usable privacy and security for ubicomp and cloud computing environments
Michael Shamos
Research Interests:
eBusiness technology, electronic voting, graph models of financial systems, experimental mathematics
Steven Wu
Research Interests:
Foundations of responsible AI, with emphasis on privacy, bias, and uncertainty considerations.
Interactive learning, including contextual bandits and reinforcement learning, and its interactions with causal inference and econometrics.
Economic aspects of machine learning, with a focus on learning in multi-agent settings.