LIRIS / INSA Lyon
Stefan Duffner
Full professor at INSA Lyon – RADYAL Project Coordinator and WP1 coordinator
Bio: Duffner is a Full Professor in the Imagine team at the LIRIS research laboratory, INSA Lyon, France, where he has been working since 2012. His research lies at the intersection of machine learning and computer vision, with a focus on object detection and tracking, similarity metric learning, and neural networks.
He holds a PhD in Computer Science from the Albert-Ludwigs-University Freiburg, completed in 2008. His doctoral research, conducted at Orange Labs in Rennes under the supervision of Dr. Christophe Garcia and Prof. Dr. Hans Burkhardt, focused on face image processing using convolutional neural networks (CNNs). His thesis was recognized by France Telecom as a “Remarkable PhD Thesis” in 2007.
Stefan’s academic path includes a Master’s degree in Applied Computer Science from the University of Freiburg, complemented by study periods at ENSICAEN in France and the University of Applied Sciences in Constance. He also gained early professional experience through industrial placements at Siemens AG and Schaefer Datentechnik in Germany.
Before joining INSA Lyon, Stefan was a postdoctoral researcher at the Idiap Research Institute in Switzerland, working on multi-face tracking in video sequences. Over the years, he has developed strong theoretical expertise in pattern recognition, image processing, and artificial neural networks, combined with practical skills in C/C++, Java, and Matlab programming. Fluent in German, English, and French, Stefan has received recognition for his work, including the Best Student Paper Award at CORESA 2005.
More info: http://u0016403263.user.hosting-agency.de/index.html
Christophe Garcia
Full professor at INSA Lyon
Bio: Christophe Garcia is a Full Professor at INSA Lyon, where he teaches computer science courses in the first cycle department, covering subjects such as computer systems, databases, algorithms, as well as advanced topics in machine learning and pattern recognition for IT students.
From 2015 to 2020, he served as Deputy Director of the LIRIS Laboratory (UMR 5205), a prominent research center jointly operated by CNRS, INSA Lyon, Université Claude Bernard Lyon 1, Université Lumière Lyon 2, and École Centrale de Lyon. Since September 2016, he has held the role of Vice-President for Research in Information and Digital Society at INSA Lyon, contributing to the strategic development of research in digital technologies. His career reflects a strong commitment to both academic leadership and education in the fields of computer science and artificial intelligence.
More info: https://christophegarciafr.wixsite.com/home-page
Martial Guidez
PhD student at INSA Lyon
Bio: Martial is a PhD student in the Imagine team at the LIRIS research laboratory, INSA Lyon, France. His research interests are in the field of software acceleration of AI applications.
He earned his Engineering degree in Modelling and Fluid-Structure Computation from the Seatech Engineering School of Toulon University.
Martial has completed a research internship in computer vision at Expleo, where he worked on deep learning perception model optimization and compression.
Inria
Marcello Traiola
Research scientist (CRCN) at the Inria Centre at Rennes University – RADYAL WP2 Coordinator
Bio: Marcello received the “Laurea” degree (MSc) in Computer Engineering in 2016 from the University of Naples Federico II, Italy, and the Ph.D. degree in Computer Engineering in 2019 from the University of Montpellier, France.
Currently, he is a tenured Research Scientist with the Inria Research Institute, at the IRISA laboratory in Rennes, France, in the TARAN research team. Previously, he was a postdoctoral researcher at Inria for one year and had also worked at the Lyon Institute of Nanotechnology, École Centrale de Lyon, in France, for almost two years.
His main research topics are emerging computing paradigms (approximate computing, in-memory computing) with a special interest in hardware design, testing, and reliability. He is a co-author of 3 book chapters, 12 articles in international journals, and more than 60 articles in international conferences and workshops. He served as a committee member and organising member at several international conferences. He serves in the IEEE/ACM DATE Executive Committee. He is an IEEE member, global coordinator of the TTTC’s E. J. McCluskey Best Doctoral Thesis Award contest and is responsible for the Test Technical Technology Community (TTTC) website.
More info: https://people.rennes.inria.fr/Marcello.Traiola/
Olivier Sentieys
Full professor at Rennes University and οn leave as Research Director (DR) at the Inria Centre at Rennes University
Bio: Olivier is a Professor at the University of Rennes and a Senior Research Director at Inria (French National Institute for Research in Digital Science and Technology). He leads the Taran team, common to Inria and the IRISA Laboratory. Until 2019, he was also the head of the “Computer Architecture” department of IRISA. His research interests are in the area of computer architectures, computer arithmetic, embedded systems, and signal processing, with a focus on system-level design, energy-efficient hardware accelerators (especially for machine learning and data mining), approximate computing (reduced-precision arithmetic, numerical accuracy analysis), and fault tolerance. He has also previously worked on power management for energy harvesting sensor networks, signal processing for communications systems, and low-power wireless (body) sensor networks. He is the author or co-author of more than 300 journal and conference papers, holds six patents, and served on the technical committees of several international IEEE/ACM/IFIP conferences, including DATE, ICCAD, and FPL. He currently serves on the DATE Executive Committee.
More info: https://people.rennes.inria.fr/Olivier.Sentieys/
Eric Rutten
Research scientist at the Inria Centre at the Inria centre at the University Grenoble Alpes
Bio: Eric is a senior researcher at INRIA Grenoble Rhône-Alpes, where he leads the Ctrl-A research team. His work focuses on the model-based control of autonomic, adaptive, and reconfigurable computing systems—an area often referred to as feedback computing. He leverages formal methods from discrete control theory, particularly discrete controller synthesis, to design correct and efficient closed-loop systems for managing computational resources, energy consumption, and fault recovery.
Eric’s research bridges theory and practice by embedding these control techniques into both model-oriented programming environments, such as the BZR reactive language, and domain-specific tools like the component-based Architecture Description Language (ADL) Ctrl-F. His goal is to make formal methods more accessible and usable through integration with model-based software engineering practices. His work spans multiple levels of computing systems: from application-level adaptation and system administration in component-based models like FRACTAL and Frascati middleware, to runtime control in high-performance computing—particularly in the dynamic tuning of parallelism and synchronization in Software Transactional Memory systems, explored within the Labex Persyval HPES project. He has also contributed to energy-efficient system administration in green data centers through the ANR Ctrl-Green project.
In the realm of embedded systems and real-time computing, Eric has worked on integrating control techniques with Real-Time Operating Systems such as Orccad. He has also made significant contributions to the design of Dynamically Partially Reconfigurable (DPR) architectures, particularly those based on FPGA platforms, through the ANR projects FAMOUS and HPeC. Before founding and leading the Ctrl-A team, he headed the Control group within the Sardes research team at INRIA.
More info: https://team.inria.fr/ctrl-a/members/eric-rutten/
Sohaib Errabii
PhD student at the Inria Centre at Rennes University
Bio: Sohaib is a PhD student at the Inria Centre at Rennes University. His research interests are in the field of hardware acceleration of AI applications. Previously, he was an R&D Software Engineer with a strong background in computer science, machine learning, and hardware design at IPOPS in Paris, having previously held research and engineering roles at INRIA as part of the DeepTrust project, where he contributed to machine learning-based digital identity verification solutions.
He earned his Master’s degree in Computer Science with high honours from ENSEIRB-MATMECA in Bordeaux, specialising in artificial intelligence. His earlier education includes rigorous training in mathematics and physics, as well as a curriculum in aerodynamics at ISAE-ENSMA.
Sohaib has completed research internships in computer vision at LABRI, where he worked on deep learning techniques to model spatial relationships between objects in images. His academic and personal projects reflect a diverse skill set, including the development of compilers, threading libraries, and time series imputation with GANs. He also has a deep interest in hardware, having implemented a RISC-V CPU core, SoC peripherals, and systolic arrays in Verilog and Amaranth.
GIPSA-lab / Université Grenoble Alpes
Bogdan Robu
Associate professor at Grenoble Alpes University – RADYAL WP3 Coordinator
Bio: Bogdan is an Associate Professor at Grenoble Alpes University (UGA) and a researcher at the GIPSA-lab in Grenoble, France, where he has been based since 2011. Before that, he spent a year as an assistant professor at Toulouse University. His research lies at the intersection of control theory and computing systems, with a focus on autonomic computing—developing self-managing systems through feedback and control mechanisms. He is also exploring how control techniques can enhance machine learning algorithms.
Bogdan earned his PhD in Automatic Control from Toulouse University in 2010, conducting his doctoral research at the LAAS laboratory on Active Vibration Control of a Flexible Fluid-Plate System.
He also holds a Master’s degree in Automatic Control and Systems Engineering from Toulouse University, and an Engineering degree in Automatic Control and Industrial Informatics from Dunărea de Jos University in Galați, Romania. His academic background is rooted in control systems, and he is currently part of the MODUS (Non-linear Systems and Complexity) research team.
More info: https://www.gipsa-lab.grenoble-inp.fr/~bogdan.robu/
Matteo Tacchi
Research scientist (CRCN) at CNRS, GIPSA-Lab
Bio: Matteo Tacchi is a CNRS researcher at GIPSA-lab in Grenoble, France, where he has been working since February 2023 within the MODUS research team, which focuses on modeling and optimal decision-making for uncertain systems. His research spans the areas of control, optimization, and applied mathematics, with particular interest in function space optimization, convex control methods, and the mathematical foundations of energy systems.
Prior to his current position, Matteo was a postdoctoral research fellow at the École Polytechnique Fédérale de Lausanne (EPFL) from 2021 to 2023, working in the Predict group led by Colin Jones at the Automatic Control Laboratory. He earned his PhD from LAAS-CNRS, completing his doctoral studies between 2017 and 2021 under the supervision of Jean Bernard Lasserre and Didier Henrion, with a focus on advanced topics in polynomial optimization and numerical analysis.
Matteo is actively engaged in various research communities and professional networks, including the CNRS Optimization network, GdR MACS, SMAI, SAGIP, IEEE, and NCCR Automation. He is also a member of the ANR-funded RADYAL project, which addresses resource-aware, dynamically adaptable machine learning. His academic work integrates theory and application, contributing to fields such as nonlinear control, computational geometry, inference methods, and the optimization and control of electrical power systems, with a particular emphasis on supporting the energy transition through mathematical innovation.
More info: https://matteotacchi.wordpress.com/
Nicola Zaupa
Postdoc at GIPSA-Lab
Bio: Nicola Zaupa is a Postdoctoral Researcher in the MODUS team at GIPSA-lab in Grenoble, France, where he is currently involved in the ANR project RADYAL. His work focuses on developing energy-aware control strategies for neural network optimisation, in collaboration with Bogdan Robu and Matteo Tacchi.
Before joining GIPSA-lab, Nicola held a postdoctoral position in the MAC team at LAAS–CNRS, where he worked with Sophie Tarbouriech and Samuele Zoboli on integrating Linear Matrix Inequality (LMI)-based control methods into neural networks. He earned his PhD at LAAS–CNRS, focusing on the control of resonant converters. His doctoral research included experimental collaboration with the Universitat Rovira i Virgili (URV) in Spain.
Nicola’s research spans mechatronics, power electronics, control, and robotics, with a strong emphasis on practical implementation and hardware validation. His interdisciplinary work reflects a commitment to bridging theoretical innovation with real-world engineering applications.
More info: https://nzaupa.github.io/