会议信息

BCD 2027: ACIS International Conference on Big Data, Cloud Computing, and Data Science

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截稿日期:
2027-02-26 还有 110 天
通知日期:
2027-04-05
会议日期:
2027-05-26
会议地点:
Las Vegas, Nevada, USA
届数:
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浏览: 14753   关注: 1   参加: 0
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会伴指数 (CP-I)

50.4 / 100
全站第 1,632 名 / 共 5,771 个会议 · 前 29%

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会议传承 (20%)
65
社区关注 (10%)
17
资料公开度 (15%)
55

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征稿

BCD 2027 (ACIS International Conference on Big Data, Cloud Computing, and Data Science) is an academic conference held in Las Vegas, Nevada, USA on 2027-05-26. The paper submission deadline is 2027-02-26. Acceptance notifications are sent on 2027-04-05.

The International Conference on Big Data, Cloud Computing, and Data Science invites researchers, academics, industry professionals, and practitioners to submit original research papers, innovative applications, and emerging perspectives addressing recent advances in big data, cloud computing, edge intelligence, artificial intelligence, and data science, with applications across emerging and transformative technologies. The conference provides a multidisciplinary forum for researchers and professionals to exchange ideas, present novel research findings, discuss emerging technologies, and explore interdisciplinary applications of data-driven computing. Topics of Interest We welcome high-quality original submissions covering, but not limited to, the following topics: Big Data and Data Analytics • Big Data Analytics and Architectures • Data Mining and Knowledge Discovery • Statistical learning, and large-scale analytics • Data Fusion and Real-Time Data Analytics • Large-Scale Data Processing and Analytics • Distributed Data Science and Data Management • Data Quality, Integration, and Governance • Graph Analytics and Network Data • High-Performance Data Analytics • Data Visualization and Decision Support • Multimodal Data Analytics • Quantum Analytic Cloud, Edge, and Distributed Computing • Cloud Computing Architectures and Services • Cloud-Native Computing • Edge Intelligence and Fog Computing • Cloud-Edge-IoT Integration • Serverless and Distributed Computing • Resource Management and Optimization • Cloud Orchestration and Virtualization • Cloud Security and Privacy • Multi-Cloud and Hybrid-Cloud Environments • Energy-Efficient and Sustainable Cloud Computing Artificial Intelligence and Machine Learning • Machine Learning and Deep Learning for Big Data • Generative AI and Large Language Models for Big Data • Multimodal Big data Analytics • Distributed and Federated Computing for Big Data Processing • Explainable and Trustworthy AI Big Data Analytics • AI Optimization and Efficient AI for Big Data and Cloud Computing • Agentic AI and Intelligent Big Data Autonomous Agents • LLM-Based Agents for Big Data Decision-Making • Trustworthy, Explainable, and Safe Agentic AI for Big Data • AI for Autonomous and Intelligent Big Data Systems Data Science and Applications • Data-Driven Decision-Making and Intelligent Analytics • Statistical Learning and Data Modeling • Data Visualization and Visual Analytics • Time-Series Analysis and Forecasting • Healthcare and Biomedical Data Science • Smart Cities and Intelligent Big Data Infrastructure • Intelligent Transportation and Autonomous Vehicles • UAVs and Aerial Autonomous Systems with Big Data Analytics • Big Data Analytics for Robotics Systems • Business, Economics, and Financial Big Data Analytics • Industrial Automation and Intelligent Manufacturing with Big Data • Environmental Monitoring and Sustainable Big Data Systems • Big Data Energy Analytics • Digital-Twin-Enabled Big Data Applications Security, Privacy, and Resilience • Big Data Security and Privacy • Cloud and Edge Security • Data Privacy, Access Control, and Security Analytics • Adversarial Machine Learning for Big Data Security • AI-Driven Cybersecurity and Big Data Security Analytics • Big Data Analytics for IoT and Cyber-Physical Systems Security • Security of Agentic Systems for Big Data • AI-Enabled Threat Intelligence and Big Data Analytics • Blockchain for Big Data Security and Analytics • Secure and Resilient Distributed Big Data Systems
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