CNS*2026 Halifax

Workshop description

Even putatively simple nervous systems exhibit a high degree of complexity that is not fully understood. The recent discovery of associative learning in box jellyfish, for example, highlights the surprisingly rich behavioural repertoire of such networks and invites a more in-depth study of the underlying neural mechanisms. These insights serve as a promising inspiration to develop technical systems that fully exploit the underlying principles of the unmatched efficiency and resilience of natural systems. 
The aim of this one-day workshop is to bring together biologists working on biological model systems with theoreticians developing approaches to understand these systems and engineers working to implement novel, non-conventional neuromorphic computing schemes and applications. Relatively simple - but resilient and efficient - nervous systems might be an excellent inspiration for edge AI, synthetic cells, sensing or miniature robotics. Therefore this workshop aims to distill principles from the evolution of the nervous system to inform theoretical insight and ultimately to design novel neuro-inspired computing hardware.

Speakers

Jan Bielecki: Seeing, Avoiding, Learning: Visual Cognition Without a Centralized Brain
P. Robin Hiesinger: Neuromorphic Growth in a Biological Brain
Vikram Chandra: Distributed neural computation and the evolution of the first brains
Celina Juliano: Hydra as a model for understanding nervous system design, function, and regeneration
Christian Klos: Smooth exact gradient descent training of spiking neural networks
Ekaterina Gribkova: Evolution of Memory: From Basic Foraging Decisions to Cognitive Map Construction
André Longtin: Online extraction of novelty: noise-cancellation the hard, biological way
Thomas Novotny: Training SNNs with exact gradients: Progress and Challenges
Sebastian Risi: From Self-Assembling Networks to Self-Adapting Machines
Marc Miskin: Learning Diffusion Models on Physical Electrical Networks.
Elisabetta Chicca: Event-Based Vision for Obstacle Avoidance and Egomotion Estimation


Here is the link to the workshop homepage.

We are very much looking to welcoming you in our workshop.

Best wishes from Kiel

Jan Steinkühler and Wilhelm Braun