We are pleased to announce that the 13th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2026) will be held in Florianópolis, Brazil, between 1st and 4th December 2026.

Recent years have witnessed significant interest in the use of Machine Learning and AI-based techniques to support large-scale data analysis, with research and implementation of systems specifically focused on supporting different phases of the data processing lifecycle. These have ranged from in-memory systems and distributed environments (e.g., MapReduce/Hadoop, Spark) to specialist environments for stream processing of data and events (e.g., Flink, Kinesis) and Serverless (e.g., OpenWhisk, AWS Lambda). We also recognize the importance of computational systems required to process small data volumes, but which involve interdependencies and relationships that are hard to capture and derive.

The International Conference on Big Data Computing, Applications and Technologies (BDCAT) is a premier annual international conference series that provides a forum for researchers from both academia and industry to present and discuss new discoveries in the broad area of big data computing and applications. The IEEE/ACM BDCAT 2026 will be held in conjunction with the 19th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2026) in Florianopolis, Brazil.

Authors are invited to submit original, unpublished research manuscripts in all areas of Big Data computing, applications, and technologies, as well as on related scaling data analysis.

Topics of interest include (but are not limited to):

1. Machine Learning and Data Mining
Data Science Models and Approaches
Supervised, Unsupervised, Semi-supervised, and Reinforcement Learning
Neural Networks, Convolution Neural Networks, and Recurrent Neural Networks
Autoencoders, Transformers, Large Language Models
Natural Language Understanding, Natural Language Processing
Swarm Intelligence and Evolutionary Strategy
Computational Efficient Model Training, Inference, and Serving
Distributed, Federated, and Parallel Learning Algorithms
Fairness, Interpretability, and Explainability

2. Data Processing and Infrastructures/Platforms
Data Acquisition, Integration, Cleaning, and Best Practices
Scalable Computing Models, Theories, and Algorithms
MapReduce: Hadoop and Spark
Privacy and Security over the Data Life Cycle
Data Search and Information Retrieval Techniques
Extract/Transform/Load (ETL) or ETL Pipelines
In-Memory Systems and Platforms
Performance Evaluation Reports
Storage Systems (including file systems, NoSQL, and RDBMS)
Resource Management Approaches
Data Analytics on Edge Devices
Fault Tolerance and Reliability
Energy-Efficiency and Sustainability
Data Archival and Preservation
Testing, Debugging, and Monitoring
Specialized Hardware for Scaling

3. Applications Domains
Internet of Things, Mobile Applications, and Cyber-Physical Systems
Healthcare and Life Science (e.g., Genome Processing)
Physical Science and Engineering
Business and Enterprise Applications
Social Network Analysis
Scientific Case Studies and Workflows
Risk Analysis and Management
Cloud-Edge Continuum
Data Streaming and Batch Applications
Data Trends and Challenges

4. Data Visualization and Analytics
Visual Analytics Algorithms and Foundations
Graph and Context Models for Visualization
Analytics Reasoning and Sense-making
Visual Representation and Interaction
Data Transformation and Presentation


Paper Submission
Submitted manuscripts must represent original and unpublished research that is not currently under review for any other conference or journal. Full papers should be submitted in PDF format, using the IEEE conference format with double-column pages including figures, tables, and references. Full papers should not exceed ten (10) pages, short papers should not exceed four (4) pages, and poster submissions should have at most two (2) pages in length. All manuscripts undergo a peer review process and will be reviewed and judged on correctness, originality, technical strength, rigor in analysis, quality of results, quality of presentation, and interest and relevance to the conference attendees.

Please submit your paper through the Easychair system: https://easychair.org/my/conference?conf=bdcat2026

Important Dates
Paper Submission Deadline: August 19, 2026
Acceptance Notification: September 30, 2026
Camera-Ready Papers Due: October 15, 2026
Conference Dates: December 1–4, 2026

Additional notes:
If Generative AI tools are used, these should be acknowledged in the paper.

At least one author of each paper must be registered for the conference and present the paper in order for the paper to be published in the proceedings. The conference proceedings will be published by the IEEE and made available online via the IEEE Xplore Digital Library.