Clarkson Center for Complex Systems Science (C3S2)

About C3S2

In brief, complex systems science involves the study of how many elements develop behaviors that are beyond those behaviors possible by considering the individual elements alone. While the behavior of each individual component of a system in isolation may support intricate dynamics, together the individual components interact to support group behaviors and system dynamics well beyond those possible from individual components alone.

Complex systems science is a rapidly growing and emerging field that is inherently interdisciplinary. It can be applied to a wide variety of fields including biology; medicine and cognitive science; mechanical, chemical, electrical and civil engineering; physics and astronomy; economics and social sciences. The future of research in these fields lies in understanding not just the isolated components of a given system, but the manner in which the individual components interact to produce emergent group behavior.

In contrast to data mining or big data, in which a primary focus is to understand hidden patterns or structure in large data sets, complex systems science attempts to identify causality and uncover the universality that exists in large-scale systems. Causality and universality are due to peer and hierarchical interactions, patterns and scaling of individual system components. Universality has been observed across a wide range of fields such as brain science, insect swarming, social science and fluid dynamics.

Key to the advancement of complex systems science is the development and use of mathematical tools designed to understand the resultant outcome of group behaviors that are not evident when studying the behavior individual elements alone. Mathematical tools for complex systems science are drawn from the following fields:

Information dynamics — the study of interaction of elements and the information flow between elements. Of particular interest is the minimum information needed to produce an outcome of important behaviors.
Algorithmic complexity — In contrast to information dynamics and entropy of evolving systems is the concept of algorithmic complexity, Komolgorov complexity and the concept of minimality of description, as a contrast that intricate behavior is often opposite to simplicity of design.
Structure and dynamics on networks — a large number of interacting parts can give rise to behaviors that emerge from the group interactions and are not implicit in any one element. Consider the collective behaviors and capabilities of an ant swarm, which is clearly not understood in terms of the behaviors of the parts. Considering networks brings in the mathematics of graph theory, but well beyond this when understanding dynamics on networks comes complexity theory.
Criticality and scaling — modelling of random networks, the implications of critical phenomena to complexity and the recent approaches to evolutionary dynamics are all part of this field. As such, understanding interactions from food webs to economies all have a universality that can be understood in terms of the science that includes hierarchical interactions. It is the characterization of such universalities that lead to complex systems as a unifying field across such disciplines.
Technical details and the tool-sets — includes areas of dynamical systems and chaos theory, network theory and graph theory, information theory, thermodynamics and statistical mechanics, cellular automata, information theory, activated processes including glasses, fractals, scaling and renormalization.

Vision & Mission

Vision

The C3S2 will be internationally recognized for fundamental contributions to the advancement of complex and systems science and the resulting impact that these contributions have in a variety of science, engineering and business applications. The C3S2 will be recognized within the University as a model for conducting collaborative interdisciplinary research.

Mission

The C3S2 mission is to encourage and facilitate research and educational opportunities in the area of complex, nonlinear, dynamical and adaptive systems. The C3S2 will foster collaboration from an interdisciplinary group of researchers to address important problems from a wide range of scientific, technological and engineering disciplines for the advancement of technology and humanity.

Specific applications of complex systems science include:

Complex and networked and multi-scaled processes
Nonlinear and chaotic systems
Information dynamics and causal inference
Systems science
Medicine and cognitive science
Biology, systems biology and mathematical epidemiology
Neuronal networks and the brain, extreme events and earthquakes, as well as cardiac arrhythmia, and more fundamentally, nonlinear chemical reaction kinetics
Mechanical, chemical, electrical and civil engineering
Fluid dynamics and turbulent systems, oceanography and meteorology, including questions of transport, modeling and sensing
Physics and astronomy
Economics and social sciences
Dynamical systems and control systems
Sensor networks, ad hoc networks and control coordination systems
Decision science, social systems and science of human groups
Adaptive and designed systems engineering
Particular examples are protein interaction networks, niche development in microbial communities, disease and rumor spreading and dynamics of innovations
Critical and rare events, mechanisms and detection, robustness and fragility

Center Motivation and Benefits to Clarkson

Dr. Erik Bollt One of the three pillars of the Clarkson@125 strategic plan is to “advance the prominence of research and scholarship.” Research centers play a key role in fostering collaboration and the growth of sponsored research. Indeed, a large majority of Clarkson’s sponsored research can be attributed to existing research centers including CAMP and CITeR, and CfM.

Dr. Erik Bollt, the inaugural C3S2 center director, has an established international reputation in the field of complex system science. Dr. Bollt’s collaborations in this field have been primarily with colleagues at other institutions. These include Princeton University, Stanford University, Oxford University, Imperial College, Bristol University, Oregon State U, Georgia Tech, Virginia Tech, Army Redstone Arsenal, Naval Research Laboratory and Los Alamos National Labs, to name several. There exists an opportunity to expand this collaboration inward to include colleagues at Clarkson in various academic departments. Doing so would provide an opportunity for Clarkson to make a greater impact in the field, thus enhancing our research reputation. A strength at Clarkson is that our culture, our size and our application-oriented philosophy all celebrate the idea that working together across fields is what we do and what we do well. This center is specifically advanced in this spirit. We will offer a venue and a means to bring us together in groupings and combinations to foster collaborations in cutting-edge research that may not otherwise take place, or even occur to specialists in individual disciplines. Together, our work can emerge strengthened as a group. Theory feeds application, and application feeds theory, and together we benefit.

Center Administration

Erik Bollt

W Jon Harrington Professor of Mathematics / Professor of Electrical & Computer Engineering / Director of the Clarkson Center for Complex Systems Science

Email: ebollt@clarkson.edu
Office: 315/268-2307