Research Interests

The current areas of research in the Complex Adaptive Systems Lab include the following:

Complex Systems:

Complex Systems Engineering

Evolvability and Modularity in Complex Systems

Multi-Agent Models of Social Networks

Self-Configuring Systems

Self-Organization and Control in Swarms

Synchronized Oscillators


AI and Neural Networks:

Embodied AI

Deep Learning

Attractor-Based Neural Computation

Developmental Learning in Neural Networks

Neural Networks in Natural Language Processing

Neural Models of Thinking and Creativity

Artificial General Intelligence

AI and Societal Issues;

AI Futures.


Computational Neuroscience & Cognitive Science:

Neuroynamical Models of Cognition

Synergistic Neural Models of Motor Control

Neuorocognitive Networks

Analysis of Large-Scale Brain Signals

Multi-Agent Models of Social Networks;

Connectionist Models of the Hippocampus

Brain-Machine Interfaces


Complex Networks:

Human Networks

Biological Networks

Language Networks

Network Clustering and Community Extraction

Network Robustness


Text Analysis and Modeling:

Semantic Analysis

Semantic Embedding

Language Models

Topic Extraction

Document Classification

Document Segmentation

Generative Models

Extraction of Ideas from Texts


Artificial Life and Computational Biology:

Artificial Organisms

Self-Organized Design

Modularity and Evolvability

Models of Evolution and Development


Last modified: January 2019