The 8th International Conference on Big Data Engineering (BDE 2026) 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
Venue
Keio University, 4-1-1 Hiyoshi, Kohoku-ku (Hiyoshi Campus), Yokohama, Japan
