Current Trends and Future Potential

Spiking Neural Networks

Organizers

Bernhard A. Moser +#, Michael Lunglmayr +, Robert Legenstein *

# Institute of Theoretical Computer Science, Graz University of Technology
+ Institute of Signal Processing, Johannes Kepler University Linz
* Software Competence Center Hagenberg (SCCH)

Workshop Description

Spiking neural networks (SNNs) compute in a fundamentally different and more biologically inspired manner than standard artificial neural networks (ANNs). They have recently gained renewed interest, mainly due to their sparse information processing, larger representation capacity, and potentially much lower computational costs.

This workshop will address the related aspect of sparsity and its impact on energy-efficient (embedded edge) AI solutions.

Key Questions to Explore

  • Are current approaches to information encoding for SNNs sufficient to address sparsity and energy efficiency in Edge AI, computer vision, and robotics?
  • SNNs are bio-inspired — but to what extent should we stick to the biological model to realize low-power edge AI?
  • What are the key mathematical differences between ANNs and traditional signal processing? Do we need a new foundation?
  • Do we need better training algorithms or better hardware support for existing ones?
  • What are the hardware challenges in enabling sparse and efficient training?
  • Despite recent progress, SNNs remain niche — are there any SNN-based killer applications coming soon?
  • What are the current trends and future potential of SNNs?

Paper Submission

We expect contributions in the form of extended abstracts that highlight the current state of work, discussions and problems. All accepted extended abstracts will be invited to submit a camera ready version of a full paper until 30th July 2025. The workshop accepts submissions in the following forms:

  1. Extended Abstract (2 - 4 pages)
  2. Full paper (approx. 8 pages)

Every contribution should be presented as a poster in the joint poster session. Submissions should use the AIRoV template.

Deadlines

  • 08. May 2025: Last opportunity to submit an extended abstract
  • 18. May 2025: Notification of acceptance
  • 07.-09. July 2025: AIRoV Symposium
  • 30. July 2025: Last opportunity to submit a full paper

Program Committee

  • Claudio Gallicchio – University of Pisa (Reservoir computing, randomized neural networks)
  • Robert Legenstein – TU Graz (Computational neuroscience)
  • Michael Lunglmayr – JKU Linz (Hardware-software co-design, edge AI)
  • Paolo Meloni – University of Cagliari (FPGAs, on-chip architectures, edge AI)
  • Angeliki Pantazi - IBM Principal Research Scientist, Manager Emerging Computing and Circuits
  • Bernhard A. Moser – SCCH & JKU Linz (Mathematical foundations of event-driven computing)
  • Osvaldo Simeone – King’s College London (Neuromorphic sensing and communications)
  • Mihai Petrivici – University of Bern (Brain-inspired computing)
  • Robert Weigel – University of Erlangen–Nürnberg (Microelectronic systems)