2025 8th International Symposium on Big Data and Applied Statistics (ISBDAS 2025)

About ISBDAS 2025

2025 8th International Symposium on Big Data and Applied Statistics


In recent years, the fields of Big Data and Applied Statistics have seen remarkable growth and evolution. Big Data has transformed from a buzzword into a critical tool across various sectors, driving significant advancements in technology, business, healthcare, and science. The ability to process and analyze vast amounts of data has led to groundbreaking insights and innovations.

Applied Statistics, as a cornerstone of data analysis, has played a crucial role in interpreting complex datasets, providing a foundation for decision-making and policy formulation. The synergy between Big Data and Applied Statistics has paved the way for more sophisticated and accurate predictive models, enhancing our understanding of complex systems.

The 2025 8th International Symposium on Big Data and Applied Statistics (ISBDAS 2025) will be held on February 28- March 2, 2025 in Guangzhou, China. The primary goal of the conference is to promote research and developmental activities in Big Data and Applied Statistics and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Big Data and Applied Statistics and related areas. We warmly invite you to participate in ISBDAS 2025.

Call For Papers

hot.gif The topics of interest include, but are not limited to:

Track : Big Data Algorithms 大数据算法

· Intelligent computing applications 智能计算应用

· Models and calculations 模型与计算

· Intelligent computing algorithms 智能计算算法

· Evolutionary computation 进化计算

· Data Mining 数据挖掘

· Ternary decision making and machine learning 三元决策与机器学习 

· Combinatorial algorithms 组合算法

· Data and text mining 数据和文本挖掘

· Knowledge reasoning 知识推理

· Deep Learning 深度学习

Track : The applied mathematics theory 应用数学理论

· Game Theory 博弈论

· Cognitive modeling and computation 认知建模与计算

· Probability and statistics 概率论与统计学

· Differential equation and their applications 微分方程及其应用

· Discrete mathematics and control 离散数学与控制

· Linear algebra and its applications 线性代数及其应用

· Numerical analysis 数值分析

· Operations Research and optimization 运筹学与优化

· Approximate theory 近似理论

· Combinatorial mathematics 组合数学

· The theory of computability 可计算性理论

· Discrete geometry离散几何

· Matrix calculations 矩阵计算

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Submission

news.gif Please send the full paper(word+pdf) to Submission System : 

Submission System (Chinese)

Submission System  (English)

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Important Dates

Full Paper Submission Date

Registration Deadline

Final Paper Submission Date

Conference Dates

December 15, 2024

January 18, 2025

January 28, 2025

February 28 - March 2, 2025

Publication

Conference Proceedings

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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 and will be submitted to IEEE Xplore, EI Compendex, Scopus for indexing.

*ISBDAS 2019:JPCS  EI Indexing   Scopus Indexing

*ISBDAS 2020:JPCS  EI Indexing   Scopus Indexing

*ISBDAS 2021:JPCS EI Indexing    Scopus Indexing

*ISBDAS 2022:JPCS  EI Indexing   Scopus Indexing

*ISBDAS 2023:JPCS  EI Indexing   Scopus Indexing

Note: All submitted articles should report original results, experimental or theoretical, not previously published or being under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of any academics. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.


Sponsor

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Guangdong AI Institute of Higher Education


Supporter


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Beijing Normal University- Artificial intelligence and future network research institute


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Beijing Normal University - Hong Kong Baptist University United International College-Artificial Intelligence and Data Science Research Hub