IJCNN 2025: Call for Position Papers!

Submission Deadline: January 15, 2025

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Call for Position Papers
IMPORTANT DATES

January 15, 2025: Paper Submission Deadline
March 31, 2025: Acceptance Notification

We are excited to announce the introduction of a Position Paper Track at the International Joint Conference on Neural Networks (IJCNN) 2025. In the rapidly evolving field of neural networks and artificial intelligence, some of the most impactful contributions come not just from novel research but from critical discussions, forward-thinking perspectives, and calls to action. This track is designed to provide a dedicated space for sharing thought-provoking viewpoints and fostering meaningful dialogue within the IJCNN community.

Position papers differ from traditional research papers in that they are evaluated based on the strength and relevance of their perspectives rather than new empirical results. We are seeking submissions that highlight important challenges, propose new directions, or spark debate on pressing issues in neural networks and AI.

Accepted position papers will be presented at the conference as oral or poster sessions and included in the conference proceedings.

Position papers may address any relevant aspect of neural networks and AI, including (but not limited to):

  • Insights into the role of biological inspiration in advancing neural networks.
  • The role of neural networks in accelerating discoveries in physics, chemistry, biology, and more.
  • Perspectives on the use and impact of generative models in application domains.
  • The importance of interpretability and explainability in safety-critical applications.
  • Evaluating the environmental impact and sustainability of current neural network models.
  • Perspectives on the adoption and limitations of neural networks in real-world applications.
  • Ethical concerns related to the design, deployment, and application of neural networks.
  • The role of regulation and policy in shaping the development of neural network technologies.
  • Recommendations for future research directions and priorities in neural networks.
View Submission Instructions
Keynote Speaker Unveiled

Max Welling
CuspAI & University of Amsterdam

Prof. Dr. Max Welling is a full professor and research chair in machine learning at the University of Amsterdam and a Merkin distinguished visiting professor at Caltech. He is co-founder and CAIO of the startup CuspAI in Materials Design.

Learn more at our website here.

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