Clarkson Complex Systems Lab

Clarkson University Center for Complex Systems Science (C3S2)

We build open tools, models, and research software for complex systems, dynamical systems, causal discovery, information theory, and scientific machine learning.

Our work connects theory and computation across nonlinear dynamics, networked systems, and time-series analysis.

Team

• Kevin Slote — Maintainer
  Applied mathematics, causal discovery, scientific machine learning, and research software.
  Help / contact: kslote1@gmail.com
  Website: www.kevin-slote.com

• Jeremie Fish — Associate Director
  Complex systems, network science, and interdisciplinary research at Clarkson.

Featured Project

CausationEntropy

A Python library for discovering causal networks from multivariate time-series data using Optimal Causation Entropy (oCSE).

• Lab GitHub: Center for Complex Systems Science
• Featured project: causationentropy

What we care about

• Dynamical systems
• Complex networks
• Causal inference from time series
• Information-theoretic methods
• Scientific open source

Contact

For help, collaboration, or questions about our tools, reach out to Kevin Slote at kslote1@gmail.com.