Goal and theme:

The aim of this workshop is to discuss and advance the state-of-the-art, research and development in the area of complex systems, with an emphasis on information flow in such structures. Of particular interest are the modeling, analysis, design and control of these complex systems. How can we model and extract relevant information from very large systems? For instance, how can we design networks that are optimal in terms of information diffusion? What are the best techniques, or hardware solutions, for such tasks? The workshop will be of interest to researchers across different disciplines, from academia as well as industry.

Complex systems are characterized by the presence of intricate interactions between their heterogeneous parts, and an overall behavior which cannot be easily explained by the properties of these individual components. For such systems, it is therefore particularly interesting to focus on how information flows between these parts, in terms of dynamical and statistical properties. This flow may represent data on a communication network, financial market interactions, gene interactions, or even a disease spreading within a population. Due to their complexity, the analysis of such systems is not trivial. They are associated with large datasets, which require advanced techniques. Similarly, prediction implies the development of refined models and simulation tools. Such developments are often only possible high-performance computing. Cloud computing also emerges as a suitable option in some cases, and several presentations at this workshop will look at these alternatives.

Scope of the Workshop:

Any submission whose content is relevant to the areas of data analysis, computational modeling, networks and complex systems will be considered, but any submission whose subject matter is related to one of the following topics will be particularly welcome:

• Analysis and modeling of large-scale networks (e.g. communication networks, social networks)
- Modeling and design of complex networks
- Tools and metrics for large networks
- Information diffusion in communication networks

• Applications to biomedical and social systems
- Network approaches in genetics and epigenetics
- Personalized medicine
- Population studies: alert systems, epidemic modeling, etc.
- Big (bio-)data: biological and medical data analysis

• New solutions for computationally-intensive problems
- HPC for data analytics
- Cloud computing
- Pre-computation in optimization problems
- Optimization approaches to complex systems

• Tools and Case-studies
- Applications, experience reports and case studies in data
- Applications, experience reports and case studies in computational modeling
- Tools for large-scale data analysis

For submission instructions, please go to http://compsac.cs.iastate.edu/cif2014.php