Outreach and Training for STEM Teachers

Clarkson's Institute for STEM Education supports the next generation of problem-solvers in STEM (science, technology, engineering and mathematics). The Institute aims to establish Clarkson as a national leader in student achievement, inclusive practices and workforce preparation.

Our faculty and staff support students in their transition into college, during their college career and post-graduation. We support America's future STEM workforce in collaboration with everyone from public school districts to industry partners.

Clarkson aims to recruit, retain and educate students from diverse backgrounds and prepare them to be teachers for K-12 and college levels.

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.

Specializing in applied mathematics, algorithms, computation and theory, Clarkson’s Department of Mathematics focuses on bringing cutting-edge research to education.

What can you do with a degree in Mathematics, Applied Mathematics and Statistics, or Data Science? More things than you can imagine. From working as an applied mathematician or statistician to furthering your education with a master's or doctorate from Clarkson, there are plenty of options at your disposal.

We consist of 18 full-time faculty and multiple dual appointments from other departments and disciplines. Consistently engaged in research, our faculty regularly present their work at seminars and colloquia.

As summer approaches, we have special programs available for incoming and continuing students:

CU Math: A Web-Based Math Refresher

Summer Math Program

Blog Post about Our Department