Complex Systems

Many important phenomena, concerning ecosystems, societies, our health, or even science itself, are more than the simple sum of their parts. Complex systems are what emerge when basic building blocks come together to generate something new. These emergent properties can be unpredictable, powerful, and even beautiful, and they are the heart of what the CU Complex Systems group seeks to understand.

ÍÃ×ÓÏÈÉú´«Ã½ÎÄ»¯×÷Æ· is home to a large and diverse research community in computational approaches to complex systems, with expertise spanning network science, collective intelligence, chaos theory, computational economics, algorithms, the science of science, social computing, and computational epidemiology.

Complex systems research at ÍÃ×ÓÏÈÉú´«Ã½ÎÄ»¯×÷Æ· is as diverse and interdisciplinary as the study of complexity itself.

Daniel Larremore and colleagues study complex network properties to understand the spread of malaria.

Daniel Larremore and colleagues study complex network properties to understand the spread of malaria.

Josh Grochow and colleagues introduced a new network statistic: the "Onion decomposition."

Josh Grochow and colleagues introduced a new network statistic: the "Onion decomposition."

Elizabeth Bradley reconstructs topological properties from systems using data gathered (which necessarily lacks infinite precision).

Elizabeth Bradley reconstructs topological properties from systems using data gathered (which necessarily lacks infinite precision).

Orit Peleg's work focuses on how multiple scales (e.g. micro, macro) of a complex system influence one another.

Orit Peleg's work focuses on how multiple scales (e.g. micro, macro) of a complex system influence one another.

Rafael Frongillo works on understanding markets and untangling many complex properties emerging within them.

Rafael Frongillo works on understanding markets and untangling many complex properties emerging within them.

Faculty in the News

Courses

  • CSCI 3352: Biological Networks
  • CSCI 4446/5446: Chaotic Dynamics
  • CSCI 4114/5114: Practical Algorithmic Complexity
  • CSCI 5423: Bio-inspired Multi-agent Systems
  • CSCI 5314/4314: Dynamic Models in Biology
  • CSCI 5352: Network Analysis and Modeling
  • CSCI 6314: Algorithmic Economics
  • CSCI 7000: Human-Centered ML 
  • CSCI 7000: AI for Science
  • CSCI 7000: Human-Centered ML
  • INFO 4613/5613: Network Science

Research:

Faculty

Affiliated Faculty

  • Nuris Figueroa-Morales (PHYS): experiments + theoretical modeling of E. coli aggregations
  • : field experiments + computational modeling of fish social networks
  • social computing, network science, and data science
  • : theoretical and computational modeling of neuronal networks