Complex adaptive systems (CAS) are all around us in the natural world as well as in engineered environments. Examples include traffic and communication networks, human organizations, markets, economies, cities, insect colonies, ecosystems, the nervous and immune systems, living organisms, and life itself.

The research conducted in the Complex Adaptive Systems Lab has two primary purposes:

The notion that complex adaptive systems can be studied as a class is based on the assumption that the same fundamental principles underlie all complex systems studied in various disciplines ranging from neuroscience to economics, molecular biology to traffic engineering, ecology to the internet. The discovery and application of these principles is the goal of complex systems research.





Director: Professor Ali A. Minai, Ph.D


Current Graduate Students:

Mei Mei (Ph.D.)
Research Area: Text Analysis.

Ulya Bayram (Ph.D.) co-advised with Prof. John Pestian
Research Area: Text Analysis.

Christopher diCesare (Ph.D.)
Research Area: Analysis of Kinematic and Kinetic Motor Synergies.

Brian Ervin (Ph.D.) co-advised with Dr. Ravi Arya
Research Area: Analysis of ECoG Signals.

Adedapo Alabi (Ph.D.) co-advised with Prof. Dieter Vanderelst
Research Area: Models of Spatial Processing in the Hippocampus.

Xiaoting Zhou (Ph.D.) co-advised with Prof. Jason Lu
Research Area: Bioinformatics and Complex Networks.

Jaswanth Yella (Ph.D.) co-advised with Prof. Anil Jegga
Research Area: Bioinformatics and Complex Networks.

Promita Mazumder (M.S.)
Research Area: Text Analysis.

Ankur Bhattacharya (M.S.)
Research Area: Social Network Modeling.

Mrinal Munbodh (M.S.)
Research Area: Text Analysis.

Adit Chawdhary (M.S.) co-advised with Prof. Anil Jegga
Research Area: Bioinformatics.

Ryan Hanzlick (M.S.)
Research Area: Deep Learning and Image Analysis.


Recent Lab Alumni:

Amer Ghanem (Ph.D. 2015)
Dissertation: Identifying Patterns of Epistemic Organization through Network-Based Analysis of Text Corpora.

Madhavun Candadai (M.S. 2015)
Thesis: ANSWER: A Cognitively-Inspired System for the Unsupervised Detection of Semantically Salient Words in Texts.

Aashay Vanarase (M.S.2016)
Thesis: CLAN: Communities in Lexical Associative Networks.

M. Furqan Afzal (M.S.2016)
Thesis: Reliable Storage and Recall of Aperiodic Spatiotemporal Activity Patterns Using Scaffolded Attractors.

Marwa Shekfeh (Ph.D. 2017)
Dissertation: MANILA: A Multi-Agent Framework for Emergent Associative Learning and Creativity in Social Networks.

Xinyu Guo (Ph.D. 2018)
Dissertation: Improved Feature-Selection for Classification Problems using Multiple Auto-Encoders.

Zhaowei Ren (M.S. 2018)
Thesis: Analysis and Modeling of the Structure of Semantic Dynamics in Texts.

Jaswanth Yella (M.S. 2018) co-advised with Prof. Anil Jegga
Thesis: Machine Learning-Based Prediction and Characterization of Drug-Drug Interactions.

Sarjoun Doumit (Ph.D. 2018)
Dissertation: IONA: Intelligent Online News Analysis.




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