Energy-Efficient AI: Models, Algorithms, and Hardware for Sustainable Intelligence

As artificial intelligence systems grow in scale and capability, their energy demands are increasing at an unsustainable pace. This workshop addresses the urgent need for energy-efficient AI, a field that seeks to develop environmentally responsible and computationally efficient approaches to machine learning. The goal is to explore innovations that reduce energy consumption across the AI stack — from models and learning algorithms to hardware implementations — while maintaining or even enhancing performance. One source of inspiration for reaching this goal is the brain, which manages to provide intelligence with 20W.

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Call for Posters

The workshop will be inclusive and accessible to a broad audience across machine learning, computer architecture, and systems engineering. Topics include but are not limited to:

This workshop aims to bring together researchers and practitioners from diverse backgrounds to foster collaboration and cross-pollination of ideas in making AI more sustainable without compromising its transformative potential.

Submission Guidelines

Important Dates

You can submit your extended abstract on the following email: Randi Goertz

Organizers: Wolfgang Maass, Marcel van Gerven

Workshop Agenda (Tentative)

The ELLIS UnConference workshop is co-located with EurIPS Copenhagen and will take place on December 2, 2025.

Time Session
8:00 - 9:00 Registration
9:00 - 10:30 Workshop talks
  Angeliki Pantazi (IBM Zurich): Designing Energy-Efficient AI: Insights from Neural Systems
  Emre Neftci (Forschungszentrum Jülich): Neuroscience-guided Learning Rules Discovery for Efficient AI
  Wilfred van der Wiel (University of Twente): Reconfigurable nonlinear processing in silicon
10:30 - 11:00 Coffee break
11:00 - 12:30 Workshop talks
  Shih-Chii Liu (ETH and University of Zurich): Brain-inspired dynamic sparsity for neuromorphic AI
  Iason Chalas (ETH and IBM Zurich): Analog In-Memory Computing for Efficient Large Language Model Deployment
  Nasir Ahmad (Radboud University Nijmegen): Two steps forward and no steps back: Training neural networks in noisy hardware without backward passes
12:30 - 13:30 Lunch
13:30 - 15:00 Workshop talks
  Yukun Yang (TU Graz): A brain-inspired method for context-aware and explainable planning that is suitable for implementation in energy-efficient AI
  Panel Discussion of the Workshop on the future of emergy-efficient AI in general, and in ELLIS
15:30 - 16:00 ELLIS Unconference Welcoming Remarks
16:00 - 18:00 ELLIS Unconference Poster Session
18:00 - 20:00 ELLIS Unconference Reception