Conference Information
BigDataService 2025: IEEE International Conference on Big Data Computing Service and Machine Learning Applications
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Submission Date:
2025-05-01
Notification Date:
2025-05-26
Conference Date:
2025-07-21
Location:
Tucson, Arizona, USA
Years:
11
Viewed: 19848   Tracked: 12   Attend: 2

Call For Papers
List of Topics (including but not limited to):

Big Data Analytics and Machine Learning

Algorithms and systems for big data analytics
Big data Machine learning, predictive and causal analytics
Visualization and visual analytics systems for big data
Knowledge modeling, extraction, discovery, analysis, and presentation
Big data Business intelligence
Optimization and agentic models for big data
Artificial intelligence models at scale
Large language models
Neuro-symbolic approaches at large scale

Integrated and Distributed Systems

Sensor networks
Internet of Things, web of things
Networking and protocols
Smart Systems (such as energy efficiency systems, smart homes, smart farms, etc.)

Big Data Platforms and Technologies

Innovative, concurrent, and scalable big data platforms
Data indexing, cleaning, transformation, and curation technologies
Big data processing frameworks and technologies
Big data services and application development methods and tools
Big data quality evaluation and assurance technologies
Big data system reliability, dependability, and availability
Open-source development and technology for big data
Big Data as a Service (BDaaS) platform and technologies

Big Data Foundations

Foundational theoretical or computational models for big data
Programming models, theories, and algorithms for big data
Standards, protocols, and quality assurance for big data

Big Data Applications and Experiences

Innovative big data applications and services in industries and domains e.g. healthcare, finance, insurance, transportation, agriculture, education, environment, multimedia, social networks, urban planning, disaster management, security
Experiences and case studies of big data applications and services
Real-world and large-scale practices of big data
Last updated by Dou Sun in 2025-06-07
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