The primary focus of the conference is on new and original research results in the areas of theoretical findings, design, implementation, and applications. Both theoretical paper and simulation (experimental) results are welcome. Topics of interest include, but are not limited to, the following：

Track 1: Data Engineering and Data Science


Big Data Management and Analytics

Data Architecture and Data Infrastructure

Data Integration and Interoperability

Cloud-Native Data Systems

Data Quality, Governance, and Stewardship

Data Mining and Knowledge Discovery

Stream Processing and Real-Time Analytics

Intelligent Data Platforms and DataOps

Scientific Data Management

Data Lakes, Data Warehouses, and Data Mesh

Data Fabric and Active Metadata

Data Observability and Data Lineage

Data Virtualization and Data Contracts

Synthetic Data Generation and Data Augmentation


Track 2: Intelligent Computing and Emerging Technologies
Distributed and Parallel Computing

Edge Intelligence and Edge AI

Federated Learning and Distributed Intelligence

High-Performance Intelligent Computing

Cloud-Edge-End Collaborative Computing

Neuromorphic Computing and Spiking Neural Networks

In-Memory and Near-Memory Computing

Quantum AI and Quantum Machine Learning

Reconfigurable Computing and Adaptive Architectures

Evolutionary Computation

Swarm Intelligence

Neuro-Symbolic AI

Causal Learning and Causal Inference

Granular Computing and Rough Sets

Approximate Computing and Precision-Scalable Computing


Track 3: AI Theory and Key Technologies
Machine Learning and Deep Learning (Supervised, Semi-supervised, Self-supervised)

Generative AI (Diffusion Models, GANs, VAEs)

Large Language Models (LLMs) and Chain-of-Thought

Foundation Models and Multimodal AI (Vision-Language, Audio-Visual)

Reinforcement Learning and Autonomous Agents

Knowledge Representation and Reasoning (Knowledge Graphs, Symbolic Reasoning)

Retrieval-Augmented Generation (RAG) and Knowledge Enhancement

Multi-Agent Systems and Collaborative Decision-Making

MLOps and LLMOps (Model Operations and Governance)

Feature Stores and Model Registries

Computer Vision and Image Analysis (recognition, understanding, classification, reconstruction, generation, etc.)


Track 4: Trustworthy AI and AI Security
Explainable and Interpretable AI

Human-Centric and Responsible AI

Cognitive Computing and Intelligent Decision Systems

Trustworthy and Secure AI

AI Safety and Reliability

Adversarial Machine Learning

AI Security and Privacy Preservation

Differential Privacy and Secure Computation

Ethical and Responsible AI Governance

Regulatory and Policy Frameworks for AI

AI Auditing and Compliance Verification

Formal Verification and Certification of AI Systems




Track 5: AI/Data-Driven Innovative Applications of Intelligent Systems
Recommender Systems and Personalized Ranking

Intelligent Dialogue Systems and Virtual Assistants

Autonomous Driving: Perception, Planning, and Control

Intelligent Robotics (Manipulation, Navigation, HRI)

Intelligent Surveillance and Anomaly Detection

AI-Assisted Diagnosis and Medical Image Analysis

Intelligent Decision Support Systems (Finance, Operations, Scheduling)

Smart Manufacturing and Industry 5.0 (Predictive Maintenance, Quality Inspection)

Smart Cities and Urban Computing (Traffic, Energy, Public Safety)

FinTech and Intelligent Risk Control

Smart Education and Learning Analytics

Digital Twin Systems and Simulation Optimization

Multimodal Interaction Systems (Speech, Vision, Haptics Fusion)

Intelligent Systems for Emergency Management and Disaster Response