Scopes
(The following topics include but are not limited to)
Track 1: Big Data Mining and Intelligent Analysis
Large-scale data mining algorithms and parallel/distributed data mining
Data stream mining, graph mining and subgraph mining
Data preprocessing, cleaning, integration and quality assessment
Data warehouse, data lake and integrated lake architecture
Time series data analysis and pattern recognition
Text, video and multimodal data mining
Big data system architecture, storage and high-performance computing
Network mining and social media analysis
Data visualization and knowledge discovery
Privacy-preserving data mining and secure computing
Scalable data mining and real-time streaming processing
Graph data management and graph learning
Track 2: Deep Learning
Deep neural network architectures and model design (CNN, RNN, Transformer, etc.)
Generative adversarial networks and diffusion models
Autoencoders and representation learning
Reinforcement learning and deep reinforcement learning
Meta-learning, transfer learning and federated learning
Multimodal learning and cross-modal alignment
Time series prediction and sequence modeling
Graph neural networks and knowledge graph representation
Large-scale pre-trained models and fine-tuning techniques
Lightweight deep learning and edge deployment
Self-supervised learning and contrastive learning
Track 3: Intelligent Decision-making
Intelligent decision support systems and real-time streaming decision engines
Automated decision-making and workflow optimization
Multi-agent collaborative decision-making and game theory
Data-driven decision-making and predictive analysis
Optimization theory and operational algorithms (multi-objective optimization, combinatorial optimization, etc.)
Risk management, resilient systems and uncertainty modeling
Human-computer collaboration and interactive decision-making
Multi-attribute decision-making and group decision-making
Interpretable artificial intelligence and trustworthy decision-making
Adversarial machine learning and robust decision-making
Blockchain and decentralized trust decision-making
Digital twin-driven intelligent decision-making applications
......
Track 1: Big Data Mining and Intelligent Analysis
Large-scale data mining algorithms and parallel/distributed data mining
Data stream mining, graph mining and subgraph mining
Data preprocessing, cleaning, integration and quality assessment
Data warehouse, data lake and integrated lake architecture
Time series data analysis and pattern recognition
Text, video and multimodal data mining
Big data system architecture, storage and high-performance computing
Network mining and social media analysis
Data visualization and knowledge discovery
Privacy-preserving data mining and secure computing
Scalable data mining and real-time streaming processing
Graph data management and graph learning
Track 2: Deep Learning
Deep neural network architectures and model design (CNN, RNN, Transformer, etc.)
Generative adversarial networks and diffusion models
Autoencoders and representation learning
Reinforcement learning and deep reinforcement learning
Meta-learning, transfer learning and federated learning
Multimodal learning and cross-modal alignment
Time series prediction and sequence modeling
Graph neural networks and knowledge graph representation
Large-scale pre-trained models and fine-tuning techniques
Lightweight deep learning and edge deployment
Self-supervised learning and contrastive learning
Track 3: Intelligent Decision-making
Intelligent decision support systems and real-time streaming decision engines
Automated decision-making and workflow optimization
Multi-agent collaborative decision-making and game theory
Data-driven decision-making and predictive analysis
Optimization theory and operational algorithms (multi-objective optimization, combinatorial optimization, etc.)
Risk management, resilient systems and uncertainty modeling
Human-computer collaboration and interactive decision-making
Multi-attribute decision-making and group decision-making
Interpretable artificial intelligence and trustworthy decision-making
Adversarial machine learning and robust decision-making
Blockchain and decentralized trust decision-making
Digital twin-driven intelligent decision-making applications
......
Important Dates/重要日期
- Submission Deadline: 2026.9.24
- Registration Deadline: 2026.10.1
- Conference Date: 2026.10.9
- Notification Date: About a week after the submission
Submission Portal/投稿方式
Mail Address: icser_eiconfs@163.com
If you have any question or need any assistance regarding the conference, please feel free to contact our conference specialists:
蒋老师
+86-15680824672(微信同号)
3761629232
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+86---(微信同号)
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