March 27-29, 2026 Hangzhou, China
The 2026 International Conference on Computational Intelligence and Machine Learning (CIML 2026), organized by Zhejiang University of Water Resources and Electric Power, will be held from March 27 to 29, 2026, in Hangzhou, China. This high-level academic event aims to unite researchers, engineers, and practitioners to exchange the latest advances and promote collaboration in the dynamic fields of computational intelligence and machine learning.
Computational intelligence—covering areas such as neural networks, fuzzy systems, evolutionary algorithms, and swarm intelligence—has become a powerful tool in addressing complex, real-world challenges. Meanwhile, machine learning continues to reshape domains including signal and image processing, natural language understanding, robotics, and smart systems, fueled by progress in deep learning, AutoML, and explainable AI.
CIML 2026 will spotlight emerging topics such as federated learning, graph neural networks, hybrid intelligent systems, and applications across robotics, healthcare, and intelligent control. The conference provides a vibrant platform to share innovative research, explore practical applications, and shape the future of intelligent computing.
January 27, 2026
February 20, 2026
February 27, 2025
March 27-29, 2026
All submissions will undergo a double-blind peer review by 2-3 experts in relevant fields. Acceptance will be based on the quality of the paper and satisfactory revisions in response to reviewers’ comments. Accepted papers, following proper registration and presentation, will be included in the conference proceedings and submitted for indexing in EI Compendex and Scopus.
Neural Networks and Deep Learning
Fuzzy Logic and Fuzzy Systems
Evolutionary Computation
Swarm Intelligence and Bio-Inspired Computation
Hybrid Intelligent Systems
Artificial Immune Systems
Cognitive and Developmental Systems
Computational Intelligence in Control Systems
Nature-Inspired Optimization Methods
Reinforcement Learning
Transfer Learning and Federated Learning
Graph Neural Networks and Deep Learning Models
Explainable AI and Model Interpretability
Machine Learning for Signal, Image, and Text Processing
AutoML and Optimization Techniques
Real-World Applications in Robotics, Healthcare, and Smart Systems
Semi-supervised Learning and Weakly-supervised Learning
Robustness and Security of Machine Learning Models
Copyright@ CIML 2026
Conference Secretary
Julian
E-mail
icciml@163.com
Phone
+86-19128974370