Independent research at the intersection of topology, applied mathematics, and complex systems.
Connect with CDTA unified detection framework that identifies emergent instabilities in real-time sensor streams through adaptive gradient and curvature analysis. The system operates within sub-millisecond latency budgets across industrial process monitoring and traffic safety domains, using domain-specific parameter profiles over a shared analytical core.
A method for characterizing graph topology through transverse-field Ising model evolution, producing distinguishable measurement distributions as structural fingerprints. The framework includes a double-blind experimental protocol with random graph controls and information-theoretic divergence metrics for statistical validation.
Persistent homology analysis applied to power grid topologies, identifying structural keystones through Vietoris-Rips complex filtration and Betti number evolution under progressive edge failure. The work characterizes how different grid geometries degrade and establishes topological invariants that predict disconnection thresholds.
An integrated approach to automated flagger assistance combining LiDAR, radar, and camera sensor fusion with real-time anomaly detection to improve work-zone safety response times. The system addresses the 800+ annual US work-zone fatalities through earlier hazard identification and optimized signal switching.
Chaos Driven Technologies is an independent research organization investigating the mathematical structures underlying complex, adaptive systems. Our work spans persistent homology, nonlinear dynamics, spectral graph theory, and edge computing — unified by an interest in how topology and geometry constrain the behavior of real-world networks.
We pursue research that is formally rigorous, experimentally falsifiable, and oriented toward measurable impact. Current investigations range from infrastructure resilience analysis to quantum-informed graph classification, with applications in industrial safety, transportation, and materials science.
For research inquiries, collaboration, or institutional interest.