Conference Information

AICM 2026: International Conference on Artificial Intelligence and Computational Modeling

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Submission Date:
2026-07-30
Notification Date:
2026-08-30
Conference Date:
2026-11-27
Location:
Hangzhou, China
Viewed: 1191   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

44.7 / 100
Ranked #2,921 of 5,682 conferences · Top 52%

#326 of 739 in Artificial Intelligence & Machine Learning

Limited evidence: this conference is not listed in CCF / ICORE / QUALIS and has no acceptance-rate data on file, so most of the score falls back to the neutral baseline.
Academic recognition (35%) No data - scored at the neutral baseline of 50
Submission selectivity (20%) No data - scored at the neutral baseline of 50
Editions held (20%) No data - scored at the neutral baseline of 50
Community attention (10%)
20
Public record completeness (15%)
35

Inputs used: Researchers who opened this page in the past 24 months: 13

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · 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 25% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-19

Call For Papers

AICM 2026 (International Conference on Artificial Intelligence and Computational Modeling) is an academic conference held in Hangzhou, China on 2026-11-27. The paper submission deadline is 2026-07-30. Acceptance notifications are sent on 2026-08-30.

AI & Computational Modeling Statistical & Computational Learning Optimization for Large-Scale Models Causal Inference & Representation Learning Neural Network Dynamics Uncertainty Quantification & Probabilistic Modeling Distributed & Federated Learning Low-Data & Self-Supervised Learning Non-Transformer Architectures World Models & Physical Consistency Computational Complexity of AI Models Trustworthy AI & Robustness Guarantees Advanced AI Models & Computational Paradigms Large Model Pre-training & Efficient Tuning Generative AI & Multimodal Modeling Graph Neural Networks & Geometric Learning Model Lightweighting MoE & Dynamic Inference Systems Brain-Inspired Computing & Neuromorphic AI for Computing & Numerical Simulation Digital Twins & Real-Time Simulation Modeling Agentic AI & Autonomous Decision-Making Edge-Cloud Collaborative AI Computing Quantum Machine Learning Models Trustworthy, Secure & Sustainable AI Explainable AI & Interpretability Adversarial Robustness & Attack-Defense Privacy-Preserving AI Model Fairness & Bias Mitigation AI Safety Alignment & Value Learning Green AI & Low-Carbon Computing Lifelong Learning & Anti-Forgetting Model Watermarking & IP Protection AI Reliability Assessment in Critical Scenarios AI Resilience Modeling in Open Environments AI & Computational Modeling Applications Smart Healthcare & Precision Medicine Autonomous Systems & Robotic Vision NLP & Speech-Language Modeling Intelligent Manufacturing & Industry 4.0 Intelligent Transportation & Autonomous Driving Smart City & Urban Computing Climate & Environmental Sustainability Smart Energy & Grid Optimization Computational Finance & Risk Prediction AI for Aerospace Engineering Simulation Cybersecurity & Threat Intelligence Smart Agriculture
Last updated by Dou Sun on

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