Theme
  	
ISSAT International Conference on Data Science and Intelligent Systems aims to provide a premier forum that brings together researchers, industry practitioners, as well as potential users of big data and advanced analytics, for discussion and exchange of ideas on the latest theoretical developments in Data Science and Intelligent Systems as well as on the best practices for a wide range of applications. Papers may address any aspect of data science and intelligent systems. Papers dealing with industrial case studies, experimental and theoretical works on data science and intelligent systems along with their application to real life situations are of particular interest.

Topics of Interest

  	  General areas and topics of interest include but are not limited to:
  	
Data Science

    Big Data modeling and prediction
    Data analytics and machine learning
    Statistical learning algorithms, models and theories
    Machine learning theories, models and systems
    Data mining, text mining and deep machine learning
    Data pre-processing and sampling
    Feature selection and development
    Large scale optimization
    High performance computing for data analytics
    Architecture and management for data science
    Web and social text mining
    Cloud computing and service data analysis
    Efficient management of data acquisition
    Intelligent analysis of large spatial data

Intelligent Systems

    Intelligent service systems and semantic computing
    Uncertainty modeling of intelligent systems
    Smart infrastructure design
    Intelligent robots and unmanned systems
    Cyber security, privacy and trust
    Intelligent vehicles and autonomous cars
    Smart industrial automation and manufacturing
    Automated data exploration and knowledge discovery
    Dependability and reliability of intelligent systems
    Human wearable sensors and technologies
    Intelligent safety systems and risk management
    Smart healthcare and energy power systems
    Human-artificial systems integration
    Intelligent pervasive and ubiquitous computing

Applications

    Large scale application case studies in intelligent systems
    Best practices and lessons learned on developing products in complex systems
    Challenges in data science and advanced analytics
    Data science and intelligent systems for real world applications