dAIEDGE, through our partner HES-SO, is organising a practical workshop on 23 March 2026 as part of the activities of section 7.3.
This workshop is aimed at SMEs and machine learning developers interested in the challenges of deploying artificial intelligence models on edge devices. The main objective is to raise awareness of existing technical limitations and provide practical tools for selecting the most suitable hardware based on performance, latency and power consumption requirements.
During the session, dAIEDGE-VLab, a tool designed to evaluate and compare the performance of AI models on different edge devices, will be presented and used. Through a practical activity, participants will learn how to set up tests, analyse results and compare different hardware platforms.
The workshop will enable attendees to understand how to optimise machine learning models for edge environments and how to evaluate their behaviour in real-world conditions. At the end of the session, participants will have solid criteria for identifying the most suitable and cost-effective platform for their use case.
The session will include an introduction to the context of edge computing, a presentation of dAIEDGE-VLab, a practical part and a final space for questions and discussion.
The workshop will be led by Dr Nuria Pazos Escudero, head of the Embedded Computing Systems Research Group at HE-Arc Ingénierie, with extensive experience in European projects such as Bonseyes and BonsAPPs; Maïck Huguenin-Vuillemin, senior researcher specialising in AI optimisation and deployment at the edge and developer of the dAIEDGE Virtual Lab; and Margaux Divernois, senior researcher with experience in industrial applications of artificial intelligence, digital twins and process optimisation.
Practical information:
- Equipment Needed: This workshop welcomes both decision-makers and developers with two pathways. For high-level exploration: laptop only required. For technical workflow: Python 3.10 installed and a development environment (such as Visual Studio Code).
- Prerequisites: Two pathways available: high-level exploration (no prerequisites) or technical hands-on (basic understanding of AI/ML pipelines and Python programming familiarity required). Presentation in English, hands-on support available in both English and French.
Places limited to 25. Register now by clicking here.
Location details will be announced soon.