Conference Information
IEEE BigData 2026: IEEE International Conference on Big Data
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Submission Date:
2026-08-21
Notification Date:
2026-10-24
Conference Date:
2026-12-14
Location:
Phoenix, Arizona, USA
Viewed: 47883   Tracked: 18   Attend: 5

Call For Papers
Topics of Interest:

Big Data Science and Foundations

New Data Standards
Data and Information Quality for Big Data
New Computational Models for Big Data
Novel Theoretical Models for Big Data

Big Data Infrastructure

Software Systems to Support Big Data Computing
New Programming Models for Big Data beyond Hadoop /MapReduce, STORM
Big Data Open Platforms
Software Techniques and Architectures in Cloud /Grid /Stream Computing
Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
Energy-efficient Computing for Big Data
Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
High Performance /Parallel Computing Platforms for Big Data
Cloud /Grid /Stream Computing for Big Data

Big Data Management

Compliance and Governance for Big Data
Multimedia and Multi-structured Data- Big Variety Data
Mobility and Big Data
Cloud/Grid/Stream Data Mining- Big Velocity Data
Large-scale Recommendation Systems and Social Media Systems
Computational Modeling and Data Integration
Data Acquisition, Integration, Cleaning, and Best Practices

Big Data Search and Mining

Search and Mining of a variety of data, multimedia data.
social, sensor /IoT /IoE, and
including scientific and engineering,

Data Ecosystem

Experimental studies of fairness, diversity, accountability, and transparency
Ecosystem assessment, valuation, and sustainability
Trust management in Big Data systems
Privacy preserving Big Data collection/analytics
Trust, resilience, privacy, and security issues
Methods for data exchange, monetization, and pricing
Ecosystem services and management
Data concepts, theory, structure, and process

Foundation Models for Big Data

Foundation Model Operationalization for multiple users
Prompt Engineering and its Management
Big data management for prompt-tuning
Big data management for fine-tuning
Big data management for pre-training

Big Data Applications

Complex Big Data Domain Applications in
Engineering
Human Resources
Cybersecurity
Industrial IoT
Media and Entertainment
Telecommunication
Advertising
Marketing
Supply Chains
Retailing
Transportation
Logistics
Education
Law
Business
Finance
Urban Planning
Smart Cities

Big Data for Science

Science Knowledge Foundation Models
AI-accelerated Simulations and Modeling
AI-Ready Scientific Big Data Systems and Analysis
Medicine and Health Science
Chemical Engineering and Synthetic Biology
Materials Informatics
Geospatial and Planetary Analytics
Climate and Earth Sciences
Genomics and Bioinformatics, Structural Biology Science
Computational Astrophysics
AI-Driven Scientific Discovery in Physical Sciences

Big Data Benchmarks

Responsible Dataset Development
Advanced Collection and Curation Practices
Data-Centric AI Methods, Tools, and Systems
Data Generators and Synthetic Environments
Benchmarking Tools and Platforms
Benchmarks and Evaluation Frameworks
New Datasets and Collections

Big Data BlueSky Ideas

Novel Interdisciplinary Synthesis
Paradigm-Shifting Applications
Foundational Assumption Challenges
New Algorithmic Opportunities
Complex and Hard Problem Solving
Trending, Emerging, Bold, or Visionary Concepts
Last updated by Dou Sun in 2026-05-12
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