Data is a valuable asset, as it is crucial to many decision making processes. In this paradigm, privacy is an important aspect of each component of a data analysis pipeline. Similarly to general security, privacy has proven to be a slippery concept, that requires a robust, mathematically rigorous approach.
Adria's research focus is on finding efficient solutions to the problem of computing on private data, that provide formal guarantees regarding information disclosure. This research touches on several areas of expertise and application domains, such as machine learning and statistics, cryptography, formal methods, databases, and systems security.