Center fоr Interacting Urban Networks

Collaboration with CCS

Led by Prof. Borja García de Soto & Prof. Sanjeev Goyal

Privacy-preserving Intra-City Collaborative Learning for Health Screening Applications
This project is aligned with the Social-Physical Nexus research cluster.
Led by Prof. Farah Shamout & Prof. Michail Maniatakos

This project aims to develop a privacy-preserving collaborative learning framework that can be applied in UAE nationwide programs that rely on data exchange, such as health screening. The work involves the development of (i) a collaborative learning framework that enables optimal training of deep neural networks, the backbone of the AI decision-support tools, across multiple parties, and (ii) a data encryption technique to facilitate secure data exchange. The team will focus on a real-world setting using data collected from multiple hospital facilities in Abu Dhabi. This study will create the basis for a novel secure data transfer and collaborative learning framework that can facilitate the exchange of a wide variety of sensitive data within smart cities. 

Become our Partner