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INTRODUCTION
AND MISSION
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:
- To understand complex adaptive systems and the
phenomena they generate through mathematical analysis and computational
modeling.
- To develop algorithms, computational models, and
artificial systems based on insights obtained from real complex systems –
especially biological systems.
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.
PEOPLE
Director: Professor Ali A. Minai, Ph.D
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.
RESEARCH ACTIVITIES
The
current areas of research in the Complex Adaptive Systems Lab include the following:
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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 |
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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. |
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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 |
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Complex
Networks: Human
Networks Biological
Networks Language
Networks Network
Clustering and Community Extraction Network
Robustness |
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Text
Analysis and Modeling: Semantic
Analysis Semantic
Embedding Language
Models Topic
Extraction Document
Classification Document
Segmentation Generative
Models Extraction
of Ideas from Texts |
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Artificial
Life and Computational Biology:
Artificial
Organisms Self-Organized
Design Modularity
and Evolvability Models
of Evolution and Development |
