9th International Conference on Big Data Engineering (BDE 2027)

The 9th International Conference on Big Data Engineering (BDE 2027) focuses on advancing theory, methodology, and practical developments in Big Data Engineering through global collaboration and knowledge sharing among researchers and practitioners.

Key Topics

• Big Data Infrastructure
  • High Performance/Parallel Computing Platforms for Big Data
  • Cloud/Grid/Stream Computing for Big Data
  • Energy-efficient Computing for Big Data
  • Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
  • Software Techniques and Architectures in Cloud/Grid/Stream Computing
  • Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
  • New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
  • Big Data Open Platforms
  • Software Systems to Support Big Data Computing
• Big Data Science and Foundations
  • New Computational Models for Big Data
  • Novel Theoretical Models for Big Data
  • New Data Standards
  • Data and Information Quality for Big Data
• Big Data Search and Mining
  • Web Search
  • Social Web Search and Mining
  • Distributed, and Peer-to-peer Search
  • Algorithms and Systems for Big Data Search
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Big Data Search Architectures, Scalability and Efficiency
  • Computational Modeling and Data Integration
  • Visualization Analytics for Big Data
  • Cloud/Grid/StreamData Mining- Big Velocity Data
  • Large-scale Recommendation Systems and Social Media Systems
  • Semantic-based Data Mining and Data Pre-processing
  • Link and Graph Mining
  • Multimedia and Multi-structured Data-Big Variety Data
  • Mobility and Big Data
• Big Data Management
  • Algorithms and Systems for Big Data Search
  • Search and Mining of variety of data including scientific and engineering, social, sensor/IoT/IoE, and multimedia data
  • Big Data Search Architectures, Scalability and Efficiency
  • Distributed, and Peer-to-peer Search
  • Visualization Analytics for Big Data
  • Data Acquisition, Integration, Cleaning, and Best Practices
  • Large-scale Recommendation Systems and Social Media Systems
  • Computational Modeling and Data Integration
  • Link and Graph Mining
  • Cloud/Grid/Stream Data Mining- Big Velocity Data
  • Mobility and Big Data
  • Semantic-based Data Mining and Data Pre-processing
  • Multimedia and Multi-structured Data- Big Variety Data
• Big Data Applications
  • Big Data Analytics in Small Business Enterprises (SMEs)
  • Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance, Business, Law, Education, Transportation, Retailing, Telecommunication
  • Real-life Case Studies of Value Creation through Big Data Analytics
  • Big Data Analytics in Government, Public Sector and Society in General
  • Big Data Industry Standards
  • Big Data as a Service
  • Experiences with Big Data Project Deployments
• Big Data Security, Privacy and Trust
  • Anomaly and APT Detection in Very Large Scale Systems
  • Intrusion Detection for Gigabit Networks
  • Visualizing Large Scale Security Data
  • High Performance Cryptography
  • Privacy Threats of Big Data
  • Threat Detection using Big Data Analytics
  • HCI Challenges for Big Data Security & Privacy
  • Privacy Preserving Big Data Collection/Analytics
  • Sociological Aspects of Big Data Privacy
  • User Studies for any of the above
  • Trust management in IoT and other Big Data Systems