Diana will present her research on technology-mediated abuse in IPV, threat models, and recent work from Cornell Tech's Intimate Partner Violence clinic.

Privacy is contextual. Everyday, we manage different contexts and adjust our privacy expectations accordingly. The theory of Contextual Integrity offers a way to capture contextual norms and a heuristic to analyze privacy. This analysis is especially helpful to detect situations in which the system designers take advantage of well-established, contextual privacy expectations, to encourage user disclosures without adhering to governing norms. For example, imagine an app that is marked to you as a patient/doctor communication tool in a medical context, yet it is actually an insurance company trying to get more information on you.

Omid is a PhD candidate at Cornell Tech working with Professor Serge Belongie. His research interests include Computer Vision, Machine Learning and Generative Models. He studies vulnerabilities of machine learning models in order to make them more robust and less dependent on (private) user data. As a Doctoral Fellow at DLI, he will explore learning models that are both accurate and resilient to various types of adversarial attacks. Omid is also a recipient of Jacobs Fellowship from Cornell University.

What happens when two different technologies, historically governed by different regulatory regimes, are combined into a single, hybrid, consumer device?