Decentralized Edge AI Infrastructure

Network Visual

The third CIS Collaboration Grant supports a collaborative research project on Decentralized Edge AI Infrastructure, with Applications in Health & Human Exposome. The goal is to create decentralized AI infrastructure as well as smart and autonomous sensors and efficient data flows to predict digital fingerprints of disease progression.

The project is directed in collaboration between 

“The idea here is to build a system and software infrastructure that allows many use cases. We want to mainly focus on health applications and human exposome while achieving the highest standards in terms of privacy, robustness, accuracy and trustworthiness. Finally, we hope to collaborate with many people on different use cases at EPFL and outside, as we want to make the results available open-source.”  Martin Jaggi 

People & Labs

The Embedded Systems Laboratory (ESL) is part of the Institute of Electrical Engineering at EPFL, and focuses on the definition of system-level multi-objective design methods, optimization methodologies and tools for high-performance embedded systems and nano-scale Multi-Processor System-on-Chip (MPSoC) architectures targeting the Internet-of-Things (IoT) Era.

The MLO lab focuses on research on scalable distributed and decentralized machine learning, optimization, deep learning, and text understanding. Algorithms developed by our team have also found adoption in industry.

The Nanoelectronic Devices Laboratory (NANOLAB) is working on research topics in advanced nanoelectronics, with special emphasis on the technology, design and modelling of nanoscale solid-state devices. The group is interested in exploring new materials, novel fabrication techniques, and novel device concepts for future applications in energy efficient Edge Artificial Intelligence, Internet-of-Things and Quantum Computing.


For questions and information on this project, please contact: [email protected]