Bordeaux, France

Energy Efficient Embedded Artificial Intelligence (E3AI)

The E3AI summer school is open to second year Master students, doctoral students, post-doctoral fellows, researchers and professionals with an interest in embedded artificial intelligence, deep learning, neuromorphic computing, natural language processing, spintronics and 6G communications.

Course content will address the consequent skill gap between embedded technology and deep learning applications, and will equip participants with the interdisciplinary knowledge and skills needed to develop innovative circuit architectures and execute data intensive applications on resource-constrained devices.

This summer school is supported by FVLLMONTI, Hermes and RadioSpin, three H2020 European projects, and is co-organised with the Green AI (GrAI) chair in artificial intelligence and the IEEE Circuits and Systems Society. The event is the first in a series of similar bi-annual events organised by and for the Embedded Artificial Intelligence (EAI) transdisciplinary community.

Target group

The course is designed for second year Master students, doctoral students, post-doctoral fellows, researchers and professionals with an interest in embedded artificial intelligence, deep learning, neuromorphic computing, natural language processing, spintronics and 6G communications.

Classes are conducted in English. Candidates should have a B2 level of English or equivalent.

Candidates must provide a CV, a short abstract of their research project and cover letter detailing their scientific interest for attending the summer school and the relevance of attending to their professional project.

Course aim

The educational objectives of the summer school reflect the highly interdisciplinary nature of the Embedded Artificial Intelligence research theme, covering on the one hand topics related to fabrication, characterisation, modelling, design, simulation and exploration of neuromorphic devices; and on the other hand application-specific topics including speech and text processing, 6G communications, and radio frequency oscillators.

The core objective of the summer school is to cover hardware-related aspects of neural networks while aiming to provide participants with a basic understanding of neural network implementation. Topics covered will include:

- Introductory aspects of neural networks
- Hardware enhancement using artificial intelligence
- Electrical characterization of functionality
- Logic cell design
- System simulation and exploration
- TCAD and compact modelling using 3D layout
- Fabrication of vertical Gate All Around (GAA) transistors
- Spintronics for hardware neural network accelerators
- 6G: design of transceivers implemented in an autonomous system
- Communications at sub-THz frequencies in CMOS technology
- Transformer architectures for machine translation and speech processing
- Applications in recognition of RF fingerprints and breast cancer

Fee info

EUR 260: Free of charge for virtual participation (only for lectures, hands-on sessions will not be available online): register here (please do not apply via the form below)

260€ for students from the University of Bordeaux (including lunch, coffee breaks and social programme costs)

260€ for IEEE CAS students (including breakfast, lunch, coffee breaks, accommodation and social programme costs)
EUR 560: 560€ for regular participants (including breakfast, lunch, coffee breaks, accommodation and social programme costs).