A selection of David Bookstaber's research across machine learning, quantitative finance, optimization, and aerospace systems, from 1993 through current preprints.
Machine Learning & AI
An empirical study of whether large language models can behaviorally recognize their own writing among sibling models of different capability tiers, establishing a measurable boundary on emergent-introspection claims. Preregistered on OSF. Data and analysis released openly.
Quantitative Finance
A quantitative study of reinsurance, property-catastrophe risk, and equity-market dependencies, for which David Bookstaber is acknowledged among the contributors.
Algorithms & Computer Science
A mathematical analysis of routing algorithms for circuit-switched and ATM cell networks.
An implementation and evaluation of simulated annealing applied to the classic combinatorial-optimization problem.
A description of a diploid genetic algorithm with performance samples and comparative analysis.
Aerospace & Human Factors
An early analysis of the costs, benefits, and technology trajectory of autonomous aerial systems.
An analysis of the human visual-perception system and how cockpit interfaces can be optimized around it.