Applied Mathematician
Formalizing hidden structures in efficiency, value, and risk—where theoretical algebra meets real-world systems. Statistics as a subset of algebraic structure.
P = W/A | z(t) = z₀e(-r+iω)t | A - L = 0
Real-world systems contain hidden algebraic structures that, once formalized, reveal exploitable asymmetries and predictable behaviors. My work applies theoretical algebra to domains typically treated as purely empirical—exposing the mathematics beneath productivity, financial value, risk distribution, and estimation.
Applied Theoretical Algebra & Statistical Systems
Clynn's Natural Law of Complex Value
A mathematical framework unifying accounting theory, information theory, and differential geometry. Commodification is formalized as informational idealization with entropy loss. Value evolution follows a continuous inward-compounding spiral embedded in rotational Godel-Einstein time-space, where every asset contains its mirror liability and systems evolve toward equilibrium.
The Inverse Relationship Between Productivity and Activity: A Mathematical Definition of Work Efficiency
Formalizes productivity as the ratio of work output to total activity (P = W/A), proving mathematically that productivity and activity are inversely correlated when work is constant. The derivative dP/dA = -W/A² demonstrates that high activity does not imply high productivity. Efficient systems minimize activity while maximizing work per unit effort.
Asymmetric Risk, Illusory Value, and the Structural Paradox of Modern Capital
Mathematical analysis of asymmetric-exposure constructs where actors achieve unbounded positive expected value by participating exclusively in upside variance while externalizing downside exposure. Demonstrates structural equivalence between casino hustlers and corporate bonus structures. Concludes that Wall Street is mathematically equivalent to—and often worse than—casino gambling due to its failure to acknowledge embedded risk asymmetries.
Gauge-Space Coarse-to-Fine Mapping for Progressive Slot Advantage
A statistical method for identifying positive-expectation regions in progressive slot machines using coarse-to-fine gauge-space mapping. Observable gauges (progressive meters, near-miss patterns) are partitioned into regions with estimated expected value across transitions, producing a tractable Markov approximation. Sequential refinement yields an increasingly precise map of exploitable states.
Two Methods for Construction Bidding: Arithmetic Summation vs. Statistical Modeling by Spec Section
Presents two workflows for estimating building-envelope scope: industry-standard arithmetic estimation (collect and sum quotes) versus statistical estimation encoding spec sections, square footage, and quote features to predict costs using historical correlations. The statistical method learns from data, produces calibrated totals with uncertainty bounds, and generates phase-level allocations—addressing the false precision inherent in arithmetic methods.
Mathematical methods applied to real-world systems
Theory implemented in practice
AI-powered project management platform for commercial glazing. Applies statistical estimation principles to automate document processing, SOV generation, and vendor matching—implementing the theoretical framework from the Construction Bidding paper.
View Demo →Ongoing work in applied mathematics, computational implementations of theoretical frameworks, and explorations at the intersection of algebra, probability, and real-world systems.
View GitHub →Interested in collaboration, research discussion, or applied mathematics consulting.