Skip to main content

Vitae

Curriculum Vitae (PDF) · Google Scholar · arXiv · ORCID · GitHub · LinkedIn

Contents

Positions

  • 2026-present, Adjunct Professor, Department of Statistics and Data Science, Wharton School, University of Pennsylvania
  • 2023-present, Visiting Scholar, Center for Computational Mathematics, Flatiron Institute
  • 2023-present, Professor, Department of Mathematical Sciences, Rutgers University-Camden
  • 2019-2021, Visiting Professor, Institute for Applied Mathematics, University of Bonn
  • 2017-2023, Associate Professor of Mathematics, Rutgers University-Camden
  • 2011-2017, Assistant Professor of Mathematics, Rutgers University-Camden
  • 2008-2011, Courant Instructor and NSF Postdoctoral Fellow, New York University
  • 2008, Guest Scientist, Freie Universität Berlin
  • 2007-2008, Postdoctoral Scholar, California Institute of Technology

Education

  • 2007, Ph.D., Applied and Computational Mathematics, California Institute of Technology
  • 2001, B.A., Computational and Applied Mathematics, Rice University
  • 2001, B.S., Mechanical Engineering, Rice University

Grants and Fellowships

  • NSF DMS-2111224, Collaborative Research: Numerical Methods for High-Dimensional Sticky Diffusions, PI, 2021-2024
  • Alexander von Humboldt Fellowship for Experienced Researchers, 2019-2021
  • NSF DMS-1816378, SPDEs and Their Numerical Solution, PI, 2018-2021
  • NSF DMS-1212058, Schemes for Brownian Dynamics with Hydrodynamic Interactions, PI, 2012-2015
  • NSF DMS-0803095, Mathematical Sciences Postdoctoral Research Fellowship, PI, 2008-2011

Honors and Awards

  • Chancellor’s Award for Outstanding Research, Rutgers University-Camden, 2022
  • Editor’s Pick, Journal of Chemical Physics, 2019 and 2020
  • Alexander von Humboldt Fellowship for Experienced Researchers, 2019-2021
  • Editor’s Choice, IMA Journal of Numerical Analysis, 2009
  • NSF Mathematical Sciences Postdoctoral Fellowship, 2008-2011
  • SIGEST Reprint, SIAM Review, 2008
  • ASCIT Teaching Award, California Institute of Technology, 2007
  • Caltech GSC Teaching and Mentoring Award, 2005
  • DOE Computational Science Graduate Fellowship, 2002-2006
  • Outstanding Sandia Labs Student Intern, 2001
  • Rice Engineering Alumni Award in Computational and Applied Mathematics, 2001

Publications

  1. Bou-Rabee, N., Mitra, S., Wibisono, A. (2026). Tail-Sensitive KL and Rényi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings. In revision, Ann. Appl. Probab.
  2. Bou-Rabee, N., Wang, Z. (2026). From Continuous to Discrete: A No-U-Turn Sampler for Permutations. Quart. Appl. Math. 84(4), 699–741. doi:10.1090/qam/1748
  3. Bou-Rabee, N., Schuh, K. (2026). Nonlinear Hamiltonian Monte Carlo and its Particle Approximation. In revision, Stoch. PDEs: Anal. Comp.
  4. Bou-Rabee, N., Carpenter, B., Kleppe, T. S., Liu, S. (2026). The Within-Orbit Adaptive Leapfrog No-U-Turn Sampler. Journal of Machine Learning Research 27, 1–64. jmlr.org
  5. Bou-Rabee, N., Carpenter, B., Marsden, M. (2026). GIST: Gibbs Self-Tuning for Locally Adaptive Hamiltonian Monte Carlo. Statist. Surv. 20, 135–179. (Survey) doi:10.1214/26-ss156
  6. Bou-Rabee, N., Eberle, A., Oberdörster, S. (2025). Accelerated Convergence in Hit-and-Run Monte Carlo and a Coordinate-free Randomized Kaczmarz Algorithm. Electron. J. Probab. 30, 1–28. doi:10.1214/25-ejp1418
  7. Bou-Rabee, N., Carpenter, B., Kleppe, T. S., Marsden, M. (2025). Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning. J. Chem. Phys. 163, 084119. doi:10.1063/5.0280793
  8. Bou-Rabee, N., Kleppe, T. S. (2025). Randomized Runge-Kutta-Nyström Methods for Unadjusted Hamiltonian and Kinetic Langevin Monte Carlo. Math. Comp. 94(356), 2839–2865. doi:10.1090/mcom/4061
  9. Bou-Rabee, N., Marsden, M. (2025). Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration. Ann. Appl. Probab. 35(1), 360–392. doi:10.1214/24-aap2116
  10. Bou-Rabee, N., Oberdörster, S. (2024). Mixing of Metropolis-Adjusted Markov Chains via Couplings: The High Acceptance Regime. Electron. J. Probab. 29, 1–27. doi:10.1214/24-ejp1150
  11. Bou-Rabee, N., Schuh, K. (2023). Convergence of Unadjusted Hamiltonian Monte Carlo for Mean-Field Models. Electron. J. Probab. 28, 1–40. doi:10.1214/23-ejp970
  12. Bou-Rabee, N., Eberle, A. (2023). Mixing Time Guarantees for Unadjusted Hamiltonian Monte Carlo. Bernoulli 29(1), 75–104. doi:10.3150/21-bej1450
  13. Bou-Rabee, N., Eberle, A. (2022). Couplings for Andersen Dynamics. Ann. Inst. Henri Poincaré (B) 58(2), 916–944. doi:10.1214/21-aihp1197
  14. Bou-Rabee, N., Eberle, A. (2021). Two-Scale Coupling for Preconditioned Hamiltonian Monte Carlo in Infinite Dimensions. Stoch. PDEs: Anal. Comp. 9, 207–242. doi:10.1007/s40072-020-00175-6
  15. Rosa-Raíces, J. L., Sun, J., Bou-Rabee, N., Miller III, T. F. (2021). A Generalized Class of Strongly Stable and Dimension-Free T-RPMD Integrators. J. Chem. Phys. 154, 024106. doi:10.1063/5.0036954
  16. Korol, R., Rosa-Raíces, J. L., Bou-Rabee, N., Miller III, T. F. (2020). Dimension-Free Path-Integral Molecular Dynamics without Preconditioning. J. Chem. Phys. 152, 104102. doi:10.1063/1.5134810
  17. Bou-Rabee, N., Holmes-Cerfon, M. (2020). Sticky Brownian Motion and its Numerical Solution. SIAM Rev. 62(1), 164–195. doi:10.1137/19m1268446
  18. Bou-Rabee, N., Eberle, A., Zimmer, R. (2020). Coupling and Convergence for Hamiltonian Monte Carlo. Ann. Appl. Probab. 30(3), 1209–1250. doi:10.1214/19-aap1528
  19. Korol, R., Bou-Rabee, N., Miller III, T. F. (2019). Cayley Modification for Strongly Stable Path-Integral and Ring-Polymer Molecular Dynamics. J. Chem. Phys. 151, 124103. doi:10.1063/1.5120282
  20. Bou-Rabee, N., Sanz-Serna, J. M. (2018). Geometric Integrators and the Hamiltonian Monte Carlo Method. Acta Numerica 27, 113–206. (Survey) doi:10.1017/s0962492917000101
  21. Bou-Rabee, N. (2018). SPECTRWM: Spectral Random Walk Method for the Numerical Solution of SPDEs. SIAM Rev. 60(2), 386–406. doi:10.1137/16m1089034
  22. Bou-Rabee, N., Vanden-Eijnden, E. (2018). Continuous-Time Random Walks for the Numerical Solution of SDEs. Mem. Amer. Math. Soc. 256(1228). doi:10.1090/memo/1228
  23. Bou-Rabee, N., Sanz-Serna, J. M. (2017). Randomized Hamiltonian Monte Carlo. Ann. Appl. Probab. 27, 2159–2194. doi:10.1214/16-aap1255
  24. Bou-Rabee, N., Donev, A., Vanden-Eijnden, E. (2014). Metropolis Integration Schemes for Self-Adjoint Diffusions. Multiscale Model. Simul. 12, 781–831. doi:10.1137/130937470
  25. Bou-Rabee, N. (2014). Time Integrators for Molecular Dynamics. Entropy 16, 138–162. doi:10.3390/e16010138
  26. Bou-Rabee, N., Hairer, M. (2012). Non-Asymptotic Mixing of the MALA Algorithm. IMA J. Numer. Anal. 33, 80–110. doi:10.1093/imanum/drs003
  27. Bou-Rabee, N., Vanden-Eijnden, E. (2012). A Patch that Imparts Unconditional Stability to Explicit Integrators for Langevin-Like Equations. J. Comput. Phys. 231, 2565–2580. doi:10.1016/j.jcp.2011.12.007
  28. Bou-Rabee, N., Vanden-Eijnden, E. (2010). Pathwise Accuracy and Ergodicity of Metropolized Integrators for SDEs. Comm. Pure Appl. Math. 63, 655–696. doi:10.1002/cpa.20306
  29. Bou-Rabee, N., Owhadi, H. (2010). Long-Run Accuracy of Variational Integrators in the Stochastic Context. SIAM J. Numer. Anal. 48, 278–297. doi:10.1137/090758842
  30. Bou-Rabee, N., Owhadi, H. (2009). Stochastic Variational Integrators. IMA J. Numer. Anal. 29, 421–443. doi:10.1093/imanum/drn018
  31. Akhmatskaya, E., Bou-Rabee, N., Reich, S. (2009). A Comparison of Generalized Hybrid Monte Carlo With and Without Momentum Flips. J. Comput. Phys. 228, 2256–2265. doi:10.1016/j.jcp.2008.12.014
  32. Bou-Rabee, N., Marsden, J. E., Romero, L. A. (2008). Dissipation-Induced Heteroclinic Orbits in Tippe Tops. SIAM Rev. (SIGEST) 50, 325–344. doi:10.1137/080716177
  33. Bou-Rabee, N., Marsden, J. E. (2008). Hamilton-Pontryagin Integrators on Lie Groups Part I: Introduction and Structure-Preserving Properties. Found. Comput. Math. 9, 197–219. doi:10.1007/s10208-008-9030-4
  34. Bou-Rabee, N., Chossat, P. (2005). The Motion of the Spherical Pendulum Subjected to a Dn Symmetric Perturbation. SIAM J. Appl. Dyn. Syst. 4, 1140–1158. doi:10.1137/040616681
  35. Bou-Rabee, N., Marsden, J. E., Romero, L. A. (2005). A Geometric Treatment of Jellett’s Egg. Z. Angew. Math. Mech. 85, 618–642. doi:10.1002/zamm.200410207
  36. Bou-Rabee, N., Marsden, J. E., Romero, L. A. (2004). Tippe Top Inversion as a Dissipation-Induced Instability. SIAM J. Appl. Dyn. Syst. 3, 352–377. doi:10.1137/030601351
  37. Bou-Rabee, N., Romero, L. A., Salinger, A. G. (2002). A Multiparameter, Numerical Stability Analysis of a Standing Cantilever Conveying Fluid. SIAM J. Appl. Dyn. Syst. 1, 190–214. doi:10.1137/s1111111102400753

Mentoring

Doctoral researchers. Students I have advised and published with, listed with their doctoral advisor and institution.

  • Katharina Schuh (Andreas Eberle, University of Bonn)
  • Stefan Oberdörster (Andreas Eberle, University of Bonn)
  • Raphael Zimmer (Andreas Eberle, University of Bonn)
  • Roy Schieven (Sonja Cox, University of Amsterdam)
  • Siddarth Mitra (Andre Wibisono, Yale University)
  • Milo Marsden (Persi Diaconis and Lexing Ying, Stanford University)
  • Jorge Rosa-Raíces (Thomas F. Miller III, California Institute of Technology)

M.S. students. All advised at the University of Bonn.

  • Solomon Jacobs
  • Zelin Ren
  • Mike Schäfer
  • Sebastian Jonas Schmidt
  • Stefan Oberdörster

Teaching

  • Wharton School, University of Pennsylvania. Probability (STAT 4300); Mathematical Statistics (STAT 4320).
  • Rutgers University-Camden. Probability and Stochastic Processes; Markov Chain Monte Carlo.
  • University of Bonn. Graduate course on Markov chain Monte Carlo.

Invited Lectures

Plenary and distinguished lectures.

  • SIAM Conference on Uncertainty Quantification (UQ26), Plenary Speaker, March 2026

A complete list of invited talks, workshops and seminars, with slides where available, is on the Talks page.

Organizing and Professional Service

  • Co-organizer, Workshop on Stochastic Computation, Foundations of Computational Mathematics (FoCM 2026), Vienna, July 2026
  • Co-organizer, Hausdorff School on MCMC: Recent Developments and New Connections, University of Bonn, September 2020
  • Organizer, contributed and invited sessions, Bayes Comp 2020, University of Florida, January 2020
  • Lecturer, SIAM Gene Golub Summer School, SPECTRWM for SPDEs, 2016
  • Lecturer, Valladolid MCMC School, MCMC-Based Integrators for SDEs, 2015
  • Organizer, Mathematics Seminar Series, Rutgers University-Camden, 2017-2019 and 2022. Invited speakers included Yuansi Chen (Duke), Sonja Cox (Amsterdam), Andreas Eberle (Bonn), Charles Epstein (Penn), Murat Erdogdu (Toronto), Miranda Holmes-Cerfon (NYU), Lina Meinecke (UC Irvine), Thomas F. Miller III (Caltech), Katherine Newhall (UNC), Qian Qin (Minnesota), Grant Rotskoff (Stanford), Jesús Sanz-Serna (UC3M), Aaron Smith (Ottawa), Santosh Vempala (Georgia Tech), Guanyang Wang (Rutgers) and Lihan Wang (Carnegie Mellon).

Refereeing and Grant Review

  • Grant reviewer for the U.S. National Science Foundation and the European Research Council.
  • Referee for journals in probability, statistics, computational mathematics and chemical physics, including Ann. Appl. Probab., Bernoulli, Electron. J. Probab., Electron. Commun. Probab., Ann. Inst. Henri Poincaré, Stoch. Process. Appl., Ann. Statist., J. R. Stat. Soc. B, Statist. Surv., J. Comput. Graph. Statist., Scand. J. Stat., J. Mach. Learn. Res., Comm. Pure Appl. Math., Comm. Math. Phys., Math. Comp., SIAM J. Sci. Comput., SIAM J. Numer. Anal., SIAM J. Appl. Math., SIAM/ASA J. Uncertain. Quantif., IMA J. Numer. Anal., Found. Comput. Math., Math. Oper. Res., Stoch. PDEs: Anal. Comp., Quart. Appl. Math., Proc. Roy. Soc. A, J. Comput. Phys. and PNAS.