Visualization of Differentially Private Data (VDPD)
Led by: Ali Sarvghad, Narges Mahyar
Current team: Mohammad Hadi Nezhad
Investigating Visual Analysis of Differentially Private Data
Differential privacy (DP) is an emerging technique for protecting sensitive data. This project investigates the principles of visual data exploration under differential privacy. In particular, we aim to understand if and how empirical visualization knowledge can be extended and adapted under DP.
If you are interested in working on or learning more about this project, please contact Ali Sarvghad at email@example.com