2026 IEEE International Conference on Big Data (IEEE BigData 2026) – Dec 14-17, 2026, Phoenix, AZ, USA (https://bigdataieee.org/BigData2026)
In recent years, “Big Data” has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately our society itself. The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data.
The IEEE Big Data 2025 (http://bigdataieee.org/BigData2025/, regular paper acceptance rate: 18%) was held at Macau, China, Dec 5-8, 2025 with more than 1200 registered participants from 54 countries
The IEEE Big Data 2024 (http://bigdataieee.org/BigData2024/, regular paper acceptance rate: 18.4%) was held at Washington DC, USA, Dec 15-18, 2024 with more than 1300 registered participants from 53 countries
The first conference, IEEE Big Data 2013, had more than 400 registered participants from 40 countries ( http://bigdataieee.org/BigData2013/), and the regular paper acceptance rate is 17.0%.
The 2026 IEEE International Conference on Big Data (IEEE BigData 2026) will continue the success of the previous IEEE Big Data conferences. It will provide a leading forum for disseminating the latest results in Big Data Research, Development, and Applications.
We solicit high-quality original research papers and significant work-in-progress papers in any aspect of Big Data with emphasis on 5Vs (Volume, Velocity, Variety, Value, and Veracity), including the Big Data challenges in scientific and engineering, social, sensor /IoT /IoE, and multimedia (audio, video, image, etc.) big data systems and applications. The conference adopts a single-blind review policy. We expect to have a very high-quality and exciting technical program at Phoenix, AZ, this year.
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
Industrial & Government Track
The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 10 pages) and extended abstracts (2-4 pages).
The Government Track welcomes papers discussing the usefulness and need for publicly contributed big data and open data, and their use. Specifically, data utilization scenarios, needs analysis, data utilization obstacle analysis and solutions, data integration processes, interfaces as data utilization solutions, visualization, use cases, evidence-based policy making, building an ecosystem for solving social issues, analyzing their cases, comparing international and regional differences, and conducting comparative surveys before and after specific events (like Covid-19). We are also looking for other big data solutions related to national and local governments and public services.
Please submit an extended abstract (2-4 pages) OR a full-length paper (up to 10 pages) through the online submission page (Industrial & Government Track dedicated page)
Paper Submission:
Please submit a full-length paper (up to 10 page IEEE 2-column format, reference pages counted in the 10 pages) through the online submission system.
https://wi-lab.com/cyberchair/2026/bigdata26/index.php
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to “formatting instructions” below). https://www.ieee.org/conferences/publishing/templates.html
Important Dates:
Electronic submission of full papers: Aug. 21, 2026
Notification of paper acceptance: Oct. 24, 2026
Camera-ready of accepted papers: Nov. 14, 2026
Conference: Dec 14-17, 2026