• International Workshop on Edge Artificial Intelligence for Industrial Applications (EAI4IA)

    Vienna 2022

Workshop Co-Chairs

Ovidiu Vermesan, SINTEF, Norway
Franz Wotawa,TU Graz, Austria
Stefan Woltran, TU Wien, Austria
Mario Diaz Nava, STM, France
Björn Debaillie, imec, Belgium


Important dates

May 30th, 2022: Submission deadline
June 10th, 2022: Acceptance information
June 24th, 2022: Author registration 
June 24th, 2022: Final paper submission 
July 25th– 26th , 2022: Workshop


Technical Committee

Cristina De Luca, Silicon Austria Labs, Austria
Ovidiu Vermesan, SINTEF, Norway
Franz Wotawa, TU Graz, Austria
Stefan Woltran, TU Wien, Austria
Mario Diaz Nava, STM, France
Björn Debaillie, imec, Belgium
Reiner John, AVL List, Austria
Marcello Coppola STM, France
Giulio Urlini, STMicroelectronics, Italy
Ilja Ocket, imec, Belgium
Sebastien Couet, imec, Belgium
Yannick Le Tiec, CEA, France
Alexandre Valentian, CEA, France
Thomas Kaempfe, Fraunhofer IPMS, Germany
Loreto Mateu, Fraunhofer-IIS, Germany
Rodrigo M. Fernandez, Fraunhofer-IIS, Germany
Luca Fanucci, University of Pisa, Italy
Giuseppe De Nicolao, University of Pavia, Italy
Davide M. Raimondo, University of Pavia, Italy
Andrea Dumbar, CSEM, Switzerland
Dennis Moolenaar, Philips, Netherland
Menno Lindwer, Grain Matter Labs, Netherland
Saad Al-Baddai, Infineon, Germany
Georg Pelz, Infineon, Germany
Christian Burmer, Infineon, Austria
Andreja Rojko, Infineon, Austria
Roman Kern, Know-Center, Austria


Call for Papers

Workshop Program




The International Workshop on Edge Artificial Intelligence for Industrial Applications (EAI4IA) is co-located with the International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI 2022) in Vienna, Austria. EAI4IA aims to bring together researchers and practitioners working on providing edge artificial intelligence methods, techniques and tools to augment industrial applications. EAI4IA comprises technical presentations, keynotes and panel discussions focusing on industrial-edge AI hardware, software and AI frameworks.


The workshop aims to create opportunities to stimulate research and innovation in the emerging domain of industrial edge AI, bringing together the research and industry communities to exchange experiences, discuss challenges and propose new research tracks to support the digitalisation of the industry and advance Society 5.0 developments. The workshop is intended as a forum where researchers and practitioners can share thoughts and experiences, discuss current and future challenges and influence industrial AI technology and operations in an open atmosphere.

The overall objective of EAI4IA is to provide a multidisciplinary venue aiming to address AI technologies at the edge, giving an overview of silicon-born AI components to advance Moore’s law and accelerate the adoption of AI-based edge processing in different industries. EAI4IA presents technological advances regarding edge AI embedded in electronic components and systems, and discusses the challenges of introducing embedded AI technologies for digitising industrial sectors.

The workshop is co-organised by three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO to provide a platform to exchange information and ideas among experts and professionals interested in fundamental advances of industrial edge AI technologies, methods, techniques and applications. Therefore, EAI4IA also aims to foster the dissemination of research results from industrial projects (also beyond the mentioned projects) and to exchange descriptions of challenges, as well as proposals for solutions for industrial projects relying on AI technology.


The topics addressed by EAI4IA are:

  • Industrial edge AI architectures.
  • Advances in AI, machine learning (ML), and deep learning (DL) to industrial edge embedded systems Edge.
  • AI requirements: intelligence, computing performance, low power design, connectivity, and safety.
  • Embedded AI edge hardware/software requirements and solutions Intelligent sensors, micro to meta edge platforms, topologies (from light edge to heavy edge).
  • Trustworthy, dependable AI for digitizing industry.
  • Edge AI tools and development platforms.
  • Edge AI software engineering aspects.
  • Business models and product strategies use cases.
  • AI-based computing embedded systems platforms to support the emerging AI algorithms and applications from system to circuit level.
  • Edge AI and IIoT platforms, intelligent connectivity, and AI integration.
  • Global standardization developments for embedded AI and their impact on industrial manufacturing.
  • Trends and roadmaps in AI-based electronic components and systems technology.
  • Best practice, practical industrial applications, implementations, and gap analysis for AI technologies.
  • Embedded AI policy issues.
  • Verification and validation methodologies for industrial AI systems.
  • Industrial AI solutions aligned with Green Deal objectives.
  • AI/ML benchmarking in Edge Computing.
  • Neuromorphic architectures and designs.