The 2019 IEEE Symposium on Immune Computation (IEEE IComputation 2019) is a part of the IEEE Symposium Series of Computational Intelligence (IEEE SSCI 2019). Immune Computation is a fast developing research area in the computational intelligence community, inspired by the information processing mechanism of biological immune system. Many of these algorithms are built on solid theoretical foundations, through understanding mathematical models and computational simulation of aspects of the immune system. The scope of this research area ranges from modeling to simulation of the immune system, to the development of novel engineering solutions to complex problems, and bridges several disciplines to provide new insights into immunology, computer science, mathematics and engineering. The aims of this symposium are: (1) to present the state-of-the-art research on immune computation; (2) to provide a forum to disseminate their recent advances and views on future perspectives in the field; (3) to offer new conceptual models for understanding the dynamics that underlie the immune system, and (4) to provide a unique event where computer scientists, engineers, immunologists, biologists, physicists, etc., may compare to each other their expertises in an interdisciplinary vision.

Topics

The topics of IEEE IComputation 2019 include two aspects. First, contributions on immune algorithms and applications are very welcome. Second, contributions on modeling biological immune systems are also welcome, but potential uses for developing computationally intelligent systems should be clearly stated. Topics of interest include, but are not limited to:

Immune algorithms and applications:

    Immune-based security techniques
    Immune-based privacy protection schemes
    Negative/positive selection algorithms
    Clonal selection algorithms
    Immune network algorithms
    Dendritic cell algorithms
    Negative databases and applications
    Negative surveys and applications
    Theoretical aspects of immune inspired algorithms
    Immune algorithms for optimization
    Immune algorithms for pattern recognition
    Immune algorithms for robotics and control
    Immune algorithms for fault diagnosis
    Immune-based data mining techniques
    Novel algorithms and new immune operators
    Benchmarking immune inspired algorithms against other techniques
    Empirical and theoretical investigations into performance and complexity of immune inspired algorithms
    Hybridization of immune inspired algorithms with other techniques

Modeling of biological immune system:

    Modeling of immune learning and memory
    Modeling of immune system response
    Modeling of immune cells and antibodies
    Modeling of viruses or cancers
    Immune network models
    Self/nonself models
    Systems & synthetic immunology
    Cellular immunology
    Vaccine design
    Immune medicine
    Chemistry immunology
    Multi-agent based models of immunity
    Security modeling of biological immune system
    Computer simulations of biological immune system