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Call for Papers | 征稿启事

Call for Papers
BDAI 2027 | October 15-17, 2027 | Chongqing, China

The BDAI 2027 is the premier interdisciplinary platform for the presentation of new advances and research results in the fields of Big Data and Artificial Intelligence. The conference will bring together leading academic scientists, researchers and scholars in the domain of interest from around the world. Topics of interest for submission include, but are not limited to:

Big Data Foundations, Systems and Management

  • Foundational models and representation formats for big data
  • Algorithms and programming techniques for big data processing
  • Big data analytics and metrics
  • Cloud computing and big data open platforms
  • Big data as a service and big data in mobile and pervasive computing
  • Big data persistence, quality and provenance control
  • Management of social network big data
  • Big data search, distributed retrieval and peer-to-peer search
  • Machine learning based on big data
  • Visualization analytics for big data
  • Big data stream processing and real-time analytics
  • Graph data management and graph computing
  • Data lakehouse and unified data architectures
  • Big data benchmarking and performance evaluation
  • Approximate query processing and sampling techniques

Data Security, Efficient Intelligence and Embodied Applications

  • Models and languages for big data protection
  • Privacy-preserving big data analytics
  • Big data encryption
  • Anomaly detection in very large scale systems
  • Collaborative threat detection using big data analytics
  • Inference optimization and acceleration for large models
  • Parameter-efficient fine-tuning and model compression
  • Green AI and energy-aware training
  • Edge intelligence and on-device deployment
  • Embodied perception and decision-making
  • Vision-language-action (VLA) models
  • World models and physical causal understanding
  • Robot learning and sim-to-real transfer
  • Spatial intelligence and 3D scene understanding
  • Big data and AI applications in media and communication

AI Foundations and Frontier Technologies

  • Machine learning and deep learning
  • Neural networks and probabilistic reasoning
  • Natural language processing
  • Knowledge representation and reasoning
  • Planning and scheduling
  • Pattern recognition and vision perception
  • Evolutionary computing and fuzzy systems
  • Hybrid intelligent systems and industrial AI applications
  • Large language models and foundation models
  • Multimodal understanding and generation
  • Retrieval-augmented generation (RAG)
  • Diffusion models and controllable content generation
  • LLM-based autonomous agents
  • Multi-agent collaboration and task planning
  • Agent memory management and tool use

Trustworthy Artificial Intelligence

  • Adversarial example generation and defense
  • Data poisoning and backdoor attack detection and defense
  • Robust training and robustness certification
  • Jailbreak attacks and defenses for large language models
  • Prompt injection and multimodal bypass defense
  • Safety alignment and red-teaming
  • Inference-time guardrails and content filtering
  • Membership inference and model extraction attack defense
  • Differential privacy and secure multi-party computation
  • Privacy-preserving training and inference in federated learning
  • Explainability and attribution analysis
  • Fairness metrics and debiasing algorithms
  • Model watermarking, fingerprinting, and machine unlearning
  • Data provenance techniques
  • Security deployment and benchmarking in critical domains (healthcare, finance, autonomous driving, ICS, etc.)