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My research operates at the intersection of high-dimensional financial time series, modern applied mathematics, and computational physics. I’ve always gravitated toward non-parametric, structure-seeking techniques—drawing on geometry, spectral methods, and ideas inspired by quantum field theory and statistical mechanics. I view financial markets as constrained dynamical systems with symmetries, coupling structures, and propagation dynamics, not as noisy regression exercises. I spent over a decade at the University of Chicago, completing Ph.D.-level coursework in economics, mathematics, and physics, including quantum field theory... more

Bio

David Sargent Wood is the Chief Quantitative Strategist and Co-Chief Technology Officer at Brooklyn Investment Group. Following Brooklyn’s 2025 acquisition, he also serves as Senior Managing Director at Nuveen. He leads the development of cutting-edge financial technology systems while managing the portfolio management team and overseeing day-to-day systematic investment management… more

Postions

Education

Research

Blog

  1. Markov processes and Kolmogorov equations
  2. Reflections for financial advisors and portfolio managers
  3. Understanding long and short margin mechanics
  4. Deep learning at scale: lesson from experiments from Perlmutter
  5. Scalable GPU programming for exascale: multi-node and multi-GPU strategies
  6. From bricolage to engineering: regularizing complexity
  7. Selling modern financial products: comparing SMAs, SaaS, and asset management
  8. From physical toil to cognitive burnout: modern labor and the ethics of software design
  9. Internal states, external worlds: concurrency, consensus, and sociotechnical challenges in computing
  10. Engineering speak: prolegomena to ideal technical discourses
  11. Self-healing computation: building resilient financial computational services
  12. Cognitive mirror: how LLMs compress language and challenge our sense of self
  13. Basis trade and treasury deleveraging
  14. The Triffin dilemma and the exorbitant privilege
  15. Client-side connection pool management
  16. Zoo keeping: dynamic assembling based on subclass attributes
  17. Go getters: a monadic way
  18. Take a walk on the functional side: yes, we need monads
  19. Working with distributed workers
  20. Cooperative concurrency with FastAPI: it's the generators, stupid
  21. Wrapping around wrappers: a primer on Python decorators
  22. Simple SSL-based encryption