Recurring themes (Adapted & Extended from NSCSI website)

The relationship of component or individual to collective behavior; the relationship of internal structure to external influence; multiscale structure and dynamics; self-similarity and fractals.

Defining complexity; characterizing the information necessary to describe the unfolding of complex systems; structuring, storing, accessing, distributing, visualizing and analyzing information describing complex systems; the dynamics of information and its computational characterization.


Time series analysis and prediction; chaos; temporal correlations; the time scale of dynamic processes; spatio-temporal patterns; dynamic scaling; pattern formation; evolution, development and adaptation; interaction between internal dynamics and external inputs; programmability of self-organization. || ||


Complex network topologies; small-world and scale-free networks; connectivity and centrality; motifs, cliques and communities; dynamical networks; adaptive networks; network modeling and analysis; modularity, degeneracy, redundancy, and substructure; visualization of networks. || ||


Computer simulation; agent-based modeling; data-driven research methods; analytical methods; nonlinear statistics; soft computing; methods and tools for complex systems education.

Additional Areas of Study

Individual automony and mutual influence

Enabling & catalyzing interactions


Emergence & leadership

Nonlinear models can describe system properties for aggregates of human interaction dynamics (HID).

Non-Linear dynamical systems

Self-similarity across scale

Complexity ideas can be applied, to human system across many levels of scale, from individual interactions, to groups, to organizations, to industries, to governments and to wholesocieties. What is uniquely complex is that their is a combined Bottom-up & top-down mutual influence.