Jaideep Vaidya

Prof. Vaidya’s research program is focused on making data, computation, and artificial intelligence SAFE (Secure, Auditable, Fair and Equitable). Today, scientific endeavors, commercial activities, and governmental interactions all rely on data collected and processed through the computing infrastructure. However, the unrestrained collection of data poses great challenges – challenges for analytics, challenges for security, and challenges for privacy and fairness. Prof. Vaidya’s primary work has been on resolving the conundrum of how to effectively make use of data while respecting the massive scope of the data as well as the privacy/security concerns of the owning entities. Starting from his initial work in privacy-preserving data mining, his work has addressed broader privacy concerns in diverse domains such as collaborative optimization, collaborative filtering, mobile computing, and biomedical informatics. Along with privacy, he is also interested in ensuring the security of information through automatic access control configuration and management, security analysis, and efficient enforcement of security policies. Furthermore, utilizing his analytics background, he has made key research contributions to the effective summarization and analysis of data, and developed technological solutions to help improve governance and enable effective emergency response. Notably, the team that he led (Team ScarletPets) developed a highly accurate and holistic financial fraud detection system, which delivered strong end-to-end privacy guarantees against a set of common threats and privacy attacks, winning the first prize in the US for the Financial Crime track of the US-UK Privacy Enhancing Technologies Challenge announced by President Joe Biden in the Summit for Democracy. Prof. Vaidya is also a member of the CASS: Cyberinfrastructure & AI for Science and Society, one of the four signature projects funded by the Rutgers New Brunswick Chancellor Challenge to build interdisciplinary scholarship and scholarly communities to serve the common good.