The IEEE CAS Seasonal School on Technologies for Artificial Intelligence tackles the critical skill gap between embedded technology and deep learning. Supported by European projects FVLLMONTI, HERMES, and RadioSpin, this event fosters a transdisciplinary community focused on embedded artificial intelligence.
Modern AI and deep learning often require extensive computing resources, impacting security and privacy. Embedded AI offers a solution by running machine learning models on edge devices, necessitating optimized software–hardware integration and energy-efficient neural network hardware. This school equips participants with the skills to innovate in circuit design and execute data-intensive applications on limited-resource devices.
The curriculum covers neural network basics, hardware enhancement, electrical characterization, and neuromorphic device design. Key topics include 6G transceiver optimization, transformer architectures for machine translation, and intelligent sensors for practical applications like RF fingerprint recognition and breast cancer detection.
Table of Contents:
1. 6G RF Roadmap and Process Technology Requests 2. Introduction to Automatic Speech Recognition 3. On-wafer Characterization of Emerging Technologies 4. Connecting Intelligences 5. Green AI: Digital Frugality
About the Author :
Dr. Francois Rivet received his Masters and the Ph.D. degrees respectively in 2005 and 2009 from the University of Bordeaux. Since June 2010, he has been tenured as Associate Professor at Bordeaux Institute of Technology (Bordeaux INP). His research is focused on the design of RFICs in the IMS Laboratory, the microelectronics laboratory of the University of Bordeaux. In 2014, he founded the “Circuits and Systems” research team with 3 faculties, 3 engineers and 8 Ph.D. students. Since 2015, he has been director of the International Office of ENSEIRB-MATMECA, the Electrical Engineering School of Bordeaux INP (1200 students). Dr. Rivet has publications in top ranked journals, international conferences, national conferences and holds 17 patents. He received the Best Paper Award at Software Defined Radio Forum in 2008 at Washington DC, USA and Journées Nationales Micro-ondes in 2015 and 2017. He is a member of several technical program committees (RFIC, ESSCIRC, …) and steering committees (RFIC, ICECS).
Cristell MANEUX received her M.Sc. degree in electronics engineering and Ph.D. degree in electronics from the University of Bordeaux, Bordeaux, France, in 1994 and 1998, respectively. From 1998 to 2012, she was Associate Professor in the IMS Laboratory, Department of Sciences and Engineering, University of Bordeaux, France. Since 2012, she has been Professor in the same laboratory, for which she has been the director since January 2022. Her research interests focus on compact modelling of advanced and emerging devices: InP HBT, SiGe HBT, carbon nanotube transistors, graphene transistors, nanowire transistors; device electrical characterization: DC, RF, pulsed, low frequency noise, RTS noise; device failure mechanisms and integrated circuit reliability; THz integrated devices for beyond 5G communications; unconventional nanoelectronics. Currently, she leads the French FerroFutures project (https://www.pepr-electronique.fr/fer/), and the European research project FVLLMONTI, call H2020 FETPROACT-09-2020 (https://fvllmonti.eu/). She has co-authored more than 200 publications on high-impact journals and conferences. She serves as Technical Program Committee member and/or reviewer for DATE, EuMW, Euro-SOI, ISCAS, NEWCAS, and ESSDERC. Since 2022, Prof. Maneux has been associate editor for IEEE Transaction of Computer Aided Design and since 2020 she has been a member of the Editorial Advisory Board of Solid State Electronics. She has also been director of the IMS-CEA LETI common lab since 2021 and has been a member of the steering committee of the IMS-ST Microelectronics common lab since 2006.
Sylvain SAÏGHI is a Professor at the University of Bordeaux and head of the “Hybrid Hardware Computing” research group. He defended his thesis in 2004 on the design of analog operators dedicated to silicon neurons. He has pioneered the development of biologically realistic and tunable silicon neurons. He is also the author and co-author of over 100 peer-reviewed publications (Google scholar: 3626 citations, h-index: 24). Thanks to a Fulbright grant, he was a visiting associate professor at Johns Hopkins University, Baltimore (MD), for six months in 2011. He was the coordinator of the European H2020 ULPEC project on ferroelectric technologies for neuromorphic computing in smart sensors. He was also an active partner in the European NEUROTECH project, which aimed to support the development of the European community in neuromorphic computing technologies. He was awarded one of the national research chairs in artificial intelligence by the French National Research Agency (ANR) as part of the French action plan for artificial intelligence. He is currently coordinator of the European RadioSpin project on the computation of neural networks using spintronic components. He is also a member of the French Emergences project on embedded artificial intelligence. This project is financed within the national framework of France 2030.
