You are kindly encouraged to contribute to and help shape the conference through submissions of your research abstracts and papers to BDSIC conference. Topics of interest for submission include, but are not limited to:

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 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 and availability
Open-source development and technology for big data
Big Data as a Service (BDaaS) platform and technologies

Big Data Analytics and Services

Algorithms and systems for big data search, analytics and visualization
Artificial Intelligence for big data and based on big data
Visualization analytics for big data
Knowledge extraction, discovery, analysis, presentation, and visualization

Big Data Applications and Experiences

Innovative big data applications and services in industries and domains healthcare, finance, insurance, transportation, agriculture, education, environment, multi-media, 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

Intelligent Computing Methodologies and Applications

Evolutionary Computing and Learning
Genetic Algorithms
Swarm Intelligence and Optimization
Independent Component Analysis
Blind Source Separation
Compressed Sensing and Sparse Coding
Natural Computing
Neural Networks
Signal Processing
Pattern Recognition
Biometrics Recognition
Image Processing
Information Security
Virtual Reality and Human-Computer Interaction
Business Intelligence and Multimedia Technology
Healthcare Informatics Theory and Methods
Unsupervised Learning
Reinforcement Learning
Machine Learning
Natural Language Processing and Computingal Linguistics
Intelligent Computing in Robotics
Intelligent Computing in Computer Vision
Intelligent Computing in Finance/Banking
Intelligent Computing in Communication Networks
Intelligent Control and Automation
Intelligent Data Fusion
Intelligent Data Analysis & Prediction
Intelligent Agent and Web Applications
Intelligent Fault Diagnosis