Kami Vaniea

Kami Vaniea

Lecturer of Cyber Security

Dr. Kami Vaniea is a Lecturer of Cyber Security at the University of Edinburgh. She maintains several interdisciplinary collaborations. She is working with the Design Informatics group to make the privacy-impacting behaviours of the Internet of Things more accessible to the general public. She is also working with people in Public Policy and Law to expand the research of cyber security research beyond the computer science academic circles.

She received her PhD from Carnegie Mellon University where she researched usable access control approaches. She then went on to be  a post-doctoral researcher at the Behaviour Information and Technology Lab at Michigan State University where she looked at the differences between self-reported security behaviours and behaviours recorded in the computer’s log files. As an Assistant Professor at Indiana University Bloomington, Dr. Vaniea looked at how people manage their online privacy through permissions. She conducted some initial research on WhatsApp privacy management in Saudi Arabia as well as privacy concerns around the “who viewed me” feature on LinkedIn.

Research Interests

Human factors of security and privacy technologies. Usability of software updates from the perspective of end-users, system administrators, and the developers that write the updates. Usability of security tools such as the APIs on security libraries and helping novice app programmers correctly implement security features. Helping users understand and manage their privacy concerns through awareness and configuration.


– 2005–2012, Doctor of Philosophy in Computer Science, Carnegie Mellon University.

– 2001–2005, Bachelor of Science in Computer Science, Oregon State University.


Chatty Factories

Our vision for the manufacturing factory of the future is to embrace the rapid growth of Internet-connected products via embedded sensors producing massive volumes of data, and transform these traditionally discrete activities into one seamless process that is capable of real-time continuous product refinement.

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