LabCompass

Nathan Glatt-Holtz

Economics, Econometrics and Finance · Indiana University

OpenAlex ORCID
Stochastic processes and financial applicationsNavier-Stokes equation solutionsFluid Dynamics and Turbulent FlowsMarkov Chains and Monte Carlo MethodsStability and Controllability of Differential Equations

Publications

81

Citations

1,103

Est. group size

—

Recurring co-author estimate

Active years

19

Publishing since 2008

Research summary
AI-generated

Nathan Glatt-Holtz works at the intersection of probability theory, partial differential equations, and computational statistics. Much of the research studies how randomness (stochastic forcing) affects fluid-flow equations like the Navier-Stokes and related models, and develops mathematical tools for analyzing their long-term behavior. A parallel line of work designs and analyzes Markov chain Monte Carlo (MCMC) sampling algorithms and applies Bayesian methods to real-world estimation problems such as inferring earthquakes from historical records or tracking virus spread.

Stochastic partial differential equations and fluid dynamicsLong-time statistical behavior and ergodicity of random systemsMarkov chain Monte Carlo (MCMC) algorithm theory and designBayesian inference for inverse and estimation problemsNumerical approximation of stochastic equations

Publication activity has been steady over the past decade, averaging around four to six papers per year with no clear upward or downward shift.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 4.2/year recently
2017: 4 publications172018: 4 publications182019: 6 publications192020: 7 publications7202021: 6 publications212022: 4 publications222023: 5 publications232024: 7 publications7242025: 3 publications252026: 2 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×22
  • The Annals of Applied Probability×2
  • Nonlinear Differential Equations and Applications NoDEA×2
  • Journal of Statistical Physics×1
  • Communications in Mathematical Physics×1

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

Claim or correct this profile