Conference Information

IJCNN 2027: International Joint Conference on Neural Networks

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Submission Date:
2027-01-31 Due in 86 days
Notification Date:
2027-03-15
Conference Date:
2027-06-14
Location:
Cape Town, South Africa
Years:
CCF: C   ICORE: B   QUALIS: A2   Viewed: 10378834   Tracked: 616   Attend: 240
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IJCNN
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Conference Partner Index (CP-I)

63.0 / 100
Ranked #515 of 5,769 conferences · Top 9%

#40 of 754 in Artificial Intelligence & Machine Learning

Academic recognition (35%)
92
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
19
Community attention (10%)
88
Public record completeness (15%)
55

Inputs used: Listed as CCF C, ICORE B, QUALIS A2 · Editions on record: 1 · Researchers following it here: 616 · Researchers who opened this page in the past 24 months: 85

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.2 · Computed 2026-11-06

Call For Papers

IJCNN 2027 (International Joint Conference on Neural Networks) is a CCF C / ICORE B / QUALIS A2 conference held in Cape Town, South Africa on 2027-06-14. The paper submission deadline is 2027-01-31. Acceptance notifications are sent on 2027-03-15.

Topics of Interest Topics of interest include but are not limited to: 1. Neural Network Fundamentals 2. Representation Learning and Generative AI 3. Foundation Models and LLMs 4. Graph and Relational Neural Networks 5. Reinforcement Learning and Decision Making 6. Continual and Adaptive Learning 7. Efficient and Resource-Constrained Neural Networks 8. Cellular, Distributed, Federated, and Scalable Learning 9. Trustworthy and Explainable AI 10. Multimodal Learning 11. Neuro-symbolic AI 12. Neuromorphic and Spiking Neural Systems 13. Computational Neuroscience, Neural Engineering, and Brain-Machine Interfaces 14. Probabilistic, Causal, and Uncertainty-Aware Learning 15. Collective and Ensemble Intelligence 16. Physics-Informed Neural Networks and Scientific ML 17. AI for X (Critical Infrastructure, Health, Education) 18. Neural Network Applications 19. Agentic AI and Embodied Intelligence 20. Quantum AI/ML
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