The 9th International Symposium on Big Data and Applied Statistics (ISBDAS 2026) will be held from March 6 to 8, 2026, in Guangzhou, China. This conference aims to establish a high-level platform for global experts, engineers, researchers, and industry professionals in “Big Data” and “Applied Statistics” to share cutting-edge research and technological innovations, track academic trends, broaden research perspectives, foster in-depth scholarly collaboration, and accelerate industrial partnerships for academic achievements.
馃敼The topics of interest for submission include, but are not limited to:
路 Big Data Analytics
路 Models, Architecture, and algorithms of Big Data
路 Big Data Search and Information Retrieval Techniques
路 Big Data Acquisition, Integration, Cleaning
路 Scalable Computing Models, Theories, and Algorithms
路 Big Data and Deep Learning
路 Big Data and High Performance Computing
路 Cyber-Infrastructure for Big Data
路 Resource Management Approaches for Big Data Systems
路 Big Data Applications for Internet of Things
路 Big Data Applications for Smart City
路 Scalability of Big Data Systems
路 Big Data Privacy and Security
路 Big Data Archival and Preservation
路 Big Data Transformation, and Presentation
路 Distributed Big Data Storage Architectures
路 High-Performance Big Data Processing Frameworks
路 Cloud Native Big Data Computing Models
路 Lossless Big Data Compression Algorithms
路 Edge – Cloud Collaborative Big Data Computing
路 Statistical Computing in Big Data Environments
路 Statistical Methods for High-Dimensional Data Analysis
路 Applications of Nonparametric Statistical Methods in Data Mining
路 Statistical Learning Theory and Algorithms
路 Statistical Software & Tool Development
路 Advanced Cluster Analysis Algorithms
路 Data Multivariate Statistical Methods
路 Statistical Data Fusion in Sensor Networks
路 Statistical Classification Algorithms in Pattern Recognition
路 Time Series Forecasting & Modeling
路 Statistical Analysis and Prediction in Power Systems
路 Statistical Modeling and Optimization in Communication Networks
路 Statistical Reliability Prediction Algorithms
馃敼Publication
All papers will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process, all accepted papers will be published by IEEE (ISBN: 979-8-3315-7218-1) and submit to EI Compendex and Scopus for indexing.
馃敼Conference E-Mail: ISBDAS@163.com