About AANN 2026
2026 6th International Conference on Advanced Algorithms and Neural Networks (AANN 2026) will be held on August 7th-9th, 2026 in Qingdao, China.
2026 6th International Conference on Advanced Algorithms and Neural Networks (AANN 2026) will be held on August 7th-9th, 2026 in Qingdao, China. AANN 2026 is to bring together innovative academics and industrial experts in the field of advanced algorithms and Neural Networks to a common forum. The primary goal of the conference is to promote research and developmental activities in advanced algorithms and Neural Networks. And another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world.The conference will be held every year to make it an ideal platform for people to share views and experiences in advanced algorithms and Neural Networks and related areas.
The conference committee invites submissions of applied or theoretical research as well as of application-oriented papers on all the topics of AANN 2026. Accepted and presented papers of AANN 2026 will be published in international conference proceedings.
Important Dates
 | Full Paper Submission Date May 22, 2026 |
 | Registration Deadline July 22, 2026 |
 | Final Paper Submission Date July 5, 2026 |
 | Conference Dates August 7-9, 2026 |
Countdown
Sponsor
Conference Topics
Advanced Algorithms
Reinforcement Learning Algorithms, Federated Learning Optimization, Evolutionary Algorithm Improvement, Swarm Intelligence Optimization, Bayesian Inference, Multi-Objective Optimization, Fuzzy Logic Algorithms, Quantum-Inspired Algorithms, Semi-Supervised Learning. Few-Shot Learning, Transfer Learning Strategies, Adversarial Learning, Constrained Optimization, Simulated Annealing, Particle Swarm Optimization, Ant Colony Optimization, Differential Evolution, Anomaly Detection, Graph Optimization Algorithms, Time-Series Prediction
Neural Networks
Convolutional Neural Networks, Recurrent Neural Networks, Transformer Architecture, Graph Neural Networks, Generative Adversarial Networks, Autoencoders, Attention Mechanisms, Deep Residual Networks, Long Short-Term Memory, Multimodal Fusion Networks, Lightweight Neural Networks, Explainable Neural Networks, Federated Neural Networks, Quantum Neural Networks, Spiking Neural Networks, Deep Belief Networks, Attention-Enhanced Networks, Contrastive Learning Networks, Multi-Task Neural Networks, Neural Architecture Search
Contact
Conference Secretary: Ms. Li | 李老师
Tel: +86-13922150104 (Wechat)
E-Mail: iicaann@163.com
If you have any questions or inquiries, please feel free to contact us.