A Complex Systems Science Company

Developing innovative technologies for distributed sensor networks and new methods for data science within supply-and-demand network systems

How are complex systems different?

Emergent

The whole is different from the sum of its parts; from Supply-and-Demand Networks to Ecological Webs, complex systems are more than simply complicated systems

Hierarchical

Due to constraints on flows, hierarchy emerges and these systems behave differently depending upon what level is considered due to emergence

Distributed

Multi-agent systems require emergent solutions to system-level challenges that can be implemented bottom-up through agent-based rules

Complexity Requires:

“A More Humble Science”

Bonini’s Paradox

"As a model of a complex system becomes more complete, it becomes less understandable. Alternatively, as a model grows more realistic, it also becomes just as difficult to understand as the real-world processes it represents,"

— John M. Dutton and William H. Starbuck

“All models are wrong, but some are useful,” — George E. P. Box

"truth is much too complicated to allow anything but approximations," — John von Neumann

"If it's simple, it's always false. If it's not, it's unusable," — Paul Valéry

Current Projects

  • Power Grid & SDN

    Full-scale flow-based modeling of grid synchronization, from synthetic smart meter generation to minimum cost power flows and synchronization backbone analysis for grid hardening with generalizations to Supply-and-Demand Networks

  • Distributed Timing Solutions

    Further developing IP and the associated hardware that would enable mission-driven decentralized network timing solutions utilizing ad-hoc P2P Software Defined Radio network messaging protocols

  • Localized Weather Prediction

    Data analytics and explainable predictive tools that leverage historical data toward understanding large scale weather patterns and localized trends using Dynamic System Language Models

  • Wearable Data Fusion

    The explosion of wearable technology has lacked the information-dense representations required to reach its true potential benefit to society and has also left wearers vulnerable to exploitation. We will address both challenges

Selected Publications

  • Spanning Trees of Recursive Scale-free Graphs

    An approach to growing spanning trees of a popular class of growing network models that enables the selection of certain features

    PRE

  • The Essential Synchronization Backbone Problem

    Minimal subgraphs of network-coupled dynamics that support stable synchronization of the original system

    Chaos

  • Emergent Hierarchy from Conductance

    By constraining the degree of a growing Barabasi-Albert model, hierarchy emerges; indicating the role played by internal conductance of subgraphs in modular networks

    NEJCS

  • Minimum Cost Percolation in Air Transportation Networks

    The application of theoretical work in network percolation to develop a framework for real-world constrained SDN system analysis

    Paper

  • Geometric Partition Entropy

    A measure-based approach to information theory in one-dimensional continuous state spaces; provides the basis for a new information science

    Entropy

  • Boltzmann-Shannon Interaction Entropy

    It all begins with an idea. Maybe you want to launch a business. Maybe you want to turn a hobby into something more.

    Chaos

  • GGPE4MI

    Generalizes the concepts from GPE to high dimensions and enables fast estimates of measure-based mutual information that capture perturbation influence

    Chaos

  • Contextual Clustering of Partial State Observations

    Context-aware clustering of sensor data by phenomenon that can incorporate expert insight to provide preprocessing for data fusion

    IEEE