Jonathan Christopher Mattingly

Jonathan Christopher Mattingly
James B. Duke Distinguished Professor

Jonathan Christopher Mattingly grew up in Charlotte, NC where he attended Irwin Ave elementary and Charlotte Country Day. He graduated from the NC School of Science and Mathematics and received a BS is Applied Mathematics with a concentration in physics from Yale University. After two years abroad with a year spent at ENS Lyon studying nonlinear and statistical physics on a Rotary Fellowship, he returned to the US to attend Princeton University where he obtained a PhD in Applied and Computational Mathematics in 1998. After 4 years as a Szego assistant professor at Stanford University and a year as a member of the IAS in Princeton, he moved to Duke in 2003. He is currently a Professor of Mathematics and of Statistical Science.

His expertise is in the longtime behavior of stochastic system including randomly forced fluid dynamics, turbulence, stochastic algorithms used in molecular dynamics and Bayesian sampling, and stochasticity in biochemical networks.

He is the recipient of a Sloan Fellowship and a PECASE CAREER award. He is also a fellow of the IMS and the AMS.

Current Appointments & Affiliations

James B. Duke Distinguished Professor, Mathematics, Trinity College of Arts & Sciences 2019
Professor of Mathematics, Mathematics, Trinity College of Arts & Sciences 2012
Chair of the Department of Mathematics, Mathematics, Trinity College of Arts & Sciences 2016

Contact Information

Background
Education, Training, & Certifications
- Ph.D., Princeton University 1998
- M.A., Princeton University 1996
- B.S., Yale University 1992
Duke Appointment History
- Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2016 - 2019
- Professor in the Department of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2012 - 2015
- Associate Professor of Mathematics, Mathematics, Trinity College of Arts & Sciences 2006 - 2012
- Associate Professor, Statistical Science, Trinity College of Arts & Sciences 2008 - 2011
- Assistant Professor of Mathematics, Mathematics, Trinity College of Arts & Sciences 2002 - 2005
Academic Positions Outside Duke
- Simons Professor , MSRI, UC Berkeley. 2015
- Visiting Professor, University de Nice. 2012
- Visiting Professor, University de Marseilles. 2010
- Visiting Professor, Berlin Summer School, TU Berlin. 2009
- Visiting Professor, University de Paris VI. 2008
- Visiting Professor, MSRI, UC Berkeley. 2007
- Principle Lecturer, Saint Flour Summer school in Probability. 2007
- Visiting Member, Centro De Giorgi, SNS Pisa, Italy. 2006
- Instructor Franco-Iranian Summer School, Zanjan, Iran. 2005
- Visiting Member, Institut Universitaire de France. 2003
- Member special year in SPDE/Tubulence, Institute for Advance Study, Princeton. 2002 - 2003
- Visiting Professor, University de Marseilles. 2002
- Visiting Scholar, Mathematics Institute, Warwick University. 2000
- NSF Post-Doctoral Fellow, Stanford University. 1999 - 2002
- Contractor, AT&T Shannon Labs. 1999
- Szego Assistant Professor of Mathematics, Stanford University. 1998 - 2002
- Post-Doctoral Member, MSRI, UC Berkely. 1998
- Summer Intern, Bell Labs, Lucent. 1996
Recognition
In the News
- MAY 7, 2019
  
  Duke Adds 21 Faculty to Distinguished Faculty Rank
- MAR 25, 2019
  
  Duke Mathematics Has Its Day in Court
- MAR 14, 2019
  
  On Pi Day at Duke, We're Talking Math!
- JUL 2, 2018 SIAM News
  
  Could Math Solve the Gerrymandering Problem?
- JUN 26, 2018 PANS News
  
  Math tools send legislators back to the drawing board
- JAN 21, 2018 City Lab
  
  How Gerrymandering Silenced North Carolina's Cities
- JAN 18, 2018 Valley News
  
  Bill wants math to guide New Hampshire’s political redistricting
- JAN 18, 2018 Nature News
  
  Maths strikes a blow for democracy
- JAN 11, 2018 Durham Harold Sun
  
  How a Duke professor helped bring down NC’s controversial Congressional map
- JAN 8, 2018 Duke Research Blog
  
  Jonathan Mattingly: The Mathematics Behind This Week's Gerrymandering Decision
- OCT 6, 2017 NY Times
  
  How Computers Turned Gerrymandering Into a Science
- JUN 1, 2017 Nature News
  
  The mathematicians who want to save democracy
- NOV 28, 2016
  
  Student Team Addresses Gerrymandering With Mathematics
- MAR 18, 2015 USA Today
  
  Duke math professor says odds of a perfect bracket are one in 2.4 trillion
- MAR 18, 2015 Chicago Sun-Times
  
  The odds of a perfect bracket? It's not 1 in 9.2 quintillion
- MAR 17, 2015
  
  News Tip: Realistic Odds of a Perfect NCAA Tournament Bracket
- MAR 17, 2015
  
  The Mathematics of the Perfect Bracket
- DEC 5, 2014 The Atlantic
  
  One of the Few Tools Left to Stop Gerrymandering Is in Peril
- NOV 26, 2014 WUNC
  
  Duke mathematicians investigate 2012 election results
- NOV 12, 2014 Greensboro News & Record
  
  Duke study puts Congressional districts under microscope
- OCT 30, 2014 WFAE-Charlotte
  
  Non-political districts would have benefited Democrats in 2012, Duke analysis shows
- OCT 30, 2014
  
  The Week at Duke {in 60 Seconds}: Countdown to Craziness; Political Math
- OCT 29, 2014
  
  Same Votes, Different Districts Would Change Results
Awards & Honors
Expertise
Subject Headings
Research
Selected Grants
- HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms awarded by National Science Foundation 2019 - 2022
- Collaborative research: Propagation of dissipation: Stochastic stabilization in finite and infinite dimensions awarded by National Science Foundation 2016 - 2020
- Quantifying Gerrymandering in the North Carolina Legislature 2019
- BIGDATA:F: Scalable Bayes uncertainty quantification with guarantees awarded by National Science Foundation 2015 - 2019
- Analysis and design of robust rare event simulation methods for protein folding and d awarded by University of Chicago 2013 - 2018
- Southeastern Probability Conference 2017: Special Edition Interacting Particle Systems with Applications in Biology, Ecology, and Statistical Physics awarded by National Science Foundation 2017 - 2018
- EMSW21-RTG: awarded by National Science Foundation 2010 - 2017
- Multiscale Analysis of Dynamic Graphs awarded by Office of Naval Research 2012 - 2016
- FRG: Collaborative Proposal: awarded by National Science Foundation 2009 - 2013
- CAREER: Stochastic Analysis and Numerics in Partial Differential Equations and Extended Dynamical Systems awarded by National Science Foundation 2005 - 2011
- Analysis of Mechanisms of Biochemical Homeostasis awarded by National Science Foundation 2006 - 2010
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Herzog, David P., and Jonathan C. Mattingly. “Ergodicity and Lyapunov Functions for Langevin Dynamics with Singular Potentials.” Communications on Pure and Applied Mathematics 72, no. 10 (October 1, 2019): 2231–55. https://doi.org/10.1002/cpa.21862.
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  - Chin, Andrew, Gregory Herschlag, and Jonathan Mattingly. “The Signature of Gerrymandering in Rucho v. Common Cause.” South Carolina Law Review 70 (2019).
  - Herschlag, G., R. Ravier, and J. C. Mattingly. “Evaluating Partisan Gerrymandering in Wisconsin,” September 2, 2017.
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  - Bakhtin, Y., T. Hurth, S. D. Lawley, and J. C. Mattingly. “Smooth invariant densities for random switching on the torus,” August 1, 2017.
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  - Johndrow, J. E., and J. C. Mattingly. “Coupling and Decoupling to bound an approximating Markov Chain,” July 31, 2017.
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  - Glatt-Holtz, N. E., D. P. Herzog, and J. C. Mattingly. “Scaling and Saturation in Infinite-Dimensional Control Problems with Applications to Stochastic Partial Differential Equations.” Annals of Pde, June 30, 2017.
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  - Glatt-Holtz, N., J. C. Mattingly, and G. Richards. “On Unique Ergodicity in Nonlinear Stochastic Partial Differential Equations.” Journal of Statistical Physics 166, no. 3–4 (February 1, 2017): 618–49. https://doi.org/10.1007/s10955-016-1605-x.
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  - Cooke, B., D. P. Herzog, J. C. Mattingly, S. A. Mckinle, and S. C. Schmidler. “Geometric ergodicity of two-dimensional hamiltonian systems with a Lennard-Jones-like repulsive potential.” Communications in Mathematical Sciences 15, no. 7 (January 1, 2017): 1987–2025. https://doi.org/10.4310/CMS.2017.v15.n7.a10.
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  - Hairer, M., and J. Mattingly. “The strong Feller property for singular stochastic PDEs,” 2016.
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  - Tempkin, J. O. B., B. V. Koten, J. C. Mattingly, A. R. Dinner, and J. Weare. “Trajectory stratification of stochastic dynamics.” Siam Review, 2016.
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  - Herzog, D. P., and J. C. Mattingly. “Noise-induced stabilization of planar flows ii.” Electronic Journal of Probability 20 (October 25, 2015). https://doi.org/10.1214/EJP.v20-4048.
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  - Bakhtin, Y., T. Hurth, and J. C. Mattingly. “Regularity of invariant densities for 1D systems with random switching.” Nonlinearity 28, no. 11 (September 30, 2015): 3755–87. https://doi.org/10.1088/0951-7715/28/11/3755.
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  - Herzog, D. P., and J. C. Mattingly. “A practical criterion for positivity of transition densities.” Nonlinearity 28, no. 8 (July 10, 2015): 2823–45. https://doi.org/10.1088/0951-7715/28/8/2823.
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  - Huckemann, S., J. C. Mattingly, E. Miller, and J. Nolen. “Sticky central limit theorems at isolated hyperbolic planar singularities.” Electronic Journal of Probability 20 (January 1, 2015). https://doi.org/10.1214/EJP.v20-3887.
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  - Lawley, S. D., J. C. Mattingly, and M. C. Reed. “Stochastic switching in infinite dimensions with applications to random parabolic PDE.” Siam Journal on Mathematical Analysis 47, no. 4 (January 1, 2015): 3035–63. https://doi.org/10.1137/140976716.
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  - Luo, S., and J. C. Mattingly. “Scaling limits of a model for selection at two scales,” 2015.
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  - Munch, E., K. Turner, P. Bendich, S. Mukherjee, J. Mattingly, and J. Harer. “Probabilistic Fréchet means for time varying persistence diagrams.” Electronic Journal of Statistics 9 (January 1, 2015): 1173–1204. https://doi.org/10.1214/15-EJS1030.
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  - Herzog, David P., and Jonathan Christopher Mattingly. “Noise-Induced Stabilization of Planar Flows II,” April 2014.
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  - Lawley, S. D., J. C. Mattingly, and M. C. Reed. “Sensitivity to switching rates in stochastically switched ODEs.” Communications in Mathematical Sciences 12, no. 7 (January 1, 2014): 1343–52. https://doi.org/10.4310/CMS.2014.v12.n7.a9.
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  - Mattingly, J. C., and E. Pardoux. “Invariant measure selection by noise. An example.” Discrete and Continuous Dynamical Systems Series A 34, no. 10 (January 1, 2014): 4223–57. https://doi.org/10.3934/dcds.2014.34.4223.
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  - Mattingly, Jonathan C., and Christy Vaughn. “Redistricting and the Will of the People.” Arxiv Preprint Arxiv:1410.8796, 2014.
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  - Hotz, Thomas, Stephan Huckemann, Huiling Le, J. S. Marron, Jonathan C. Mattingly, Ezra Miller, James Nolen, Megan Owen, Vic Patrangenaru, and Sean Skwerer. “Sticky central limit theorems on open books.” The Annals of Applied Probability 23 (2013): 2238–58. https://doi.org/10.1214/12-AAP899.
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  - Mattingly, J. C., S. A. McKinley, and N. S. Pillai. “Geometric ergodicity of a bead-spring pair with stochastic Stokes forcing.” Stochastic Processes and Their Applications 122, no. 12 (December 1, 2012): 3953–79. https://doi.org/10.1016/j.spa.2012.07.003.
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  - Luo, Shishi, Michael Reed, Jonathan C. Mattingly, and Katia Koelle. “The impact of host immune status on the within-host and population dynamics of antigenic immune escape..” J R Soc Interface 9, no. 75 (October 7, 2012): 2603–13. https://doi.org/10.1098/rsif.2012.0180.
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  - Athreyaz, A., T. Kolba, and J. C. Mattingly. “Propagating lyapunov functions to prove noise-induced stabilization.” Electronic Journal of Probability 17 (2012). https://doi.org/10.1214/EJP.v17-2410.
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  - Porporato, A., P. R. Kramer, M. Cassiani, E. Daly, and J. Mattingly. “Local kinetic interpretation of entropy production through reversed diffusion..” Phys Rev E Stat Nonlin Soft Matter Phys 84, no. 4 Pt 1 (October 2011). https://doi.org/10.1103/PhysRevE.84.041142.
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  - Anderson, D. F., and J. C. Mattingly. “A weak trapezoidal method for a class of stochastic differential equations.” Communications in Mathematical Sciences 9, no. 1 (2011): 301–18.
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  - Hairer, M., J. C. Mattingly, and M. Scheutzow. “Asymptotic coupling and a general form of Harris' theorem with applications to stochastic delay equations.” Probability Theory and Related Fields 149, no. 1 (2011): 223–59. https://doi.org/10.1007/s00440-009-0250-6.
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  - Hairer, M., and J. C. Mattingly. “A theory of hypoellipticity and unique ergodicity for semilinear stochastic PDEs.” Electronic Journal of Probability 16 (2011): 658–738.
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  - Hairer, Martin, and Jonathan C. Mattingly. “Yet Another Look at Harris’ Ergodic Theorem for Markov Chains,” 2011, 109–17. https://doi.org/10.1007/978-3-0348-0021-1_7.
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  - Koelle, K., O. Ratmann, D. A. Rasmussen, V. Pasour, and J. Mattingly. “A dimensionless number for understanding the evolutionary dynamics of antigenically variable RNA viruses.” Proceedings of the Royal Society B: Biological Sciences 278, no. 1725 (2011): 3723–30. https://doi.org/10.1098/rspb.2011.0435.
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  - Mattingly, J. C., A. M. Stuart, and M. V. Tretyakov. “Convergence of numerical time-averaging and stationary measures via Poisson equations.” Siam Journal on Numerical Analysis 48, no. 2 (2010): 552–77. https://doi.org/10.1137/090770527.
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  - Hairer, M., and J. C. Mattingly. “Slow energy dissipation in anharmonic oscillator chains.” Communications on Pure and Applied Mathematics 62, no. 8 (2009): 999–1032. https://doi.org/10.1002/cpa.20280.
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  - Iyer, G., and J. Mattingly. “A stochastic-Lagrangian particle system for the Navier-Stokes equations.” Nonlinearity 21, no. 11 (November 1, 2008): 2537–53. https://doi.org/10.1088/0951-7715/21/11/004.
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  - Martin Hairer, Jonathan C. “Spectral gaps in Wasserstein distances and the 2D stochastic Navier-Stokes equations.” Annals of Probability, no. 6 (2008): 993–1032.
  - Mattingly, J. C., T. Suidan, and E. Vanden-Eijnden. “Simple systems with anomalous dissipation and energy cascade.” Communications in Mathematical Physics 276, no. 1 (November 1, 2007): 189–220. https://doi.org/10.1007/s00220-007-0333-0.
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  - Bakhtin, Y., and J. C. Mattingly. “Malliavin calculus for infinite-dimensional systems with additive noise.” Journal of Functional Analysis 249, no. 2 (August 15, 2007): 307–53. https://doi.org/10.1016/j.jfa.2007.02.011.
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  - Anderson, David F., Jonathan C. Mattingly, H Frederik Nijhout, and Michael C. Reed. “Propagation of fluctuations in biochemical systems, I: linear SSC networks..” Bulletin of Mathematical Biology 69, no. 6 (August 2007): 1791–1813. https://doi.org/10.1007/s11538-007-9192-2.
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  - Lamba, H., J. C. Mattingly, and A. M. Stuart. “An adaptive Euler-Maruyama scheme for SDEs: Convergence and stability.” Ima Journal of Numerical Analysis 27, no. 3 (July 1, 2007): 479–506. https://doi.org/10.1093/imanum/drl032.
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  - Anderson, D. F., and J. C. Mattingly. “Propagation of fluctuations in biochemical systems, II: Nonlinear chains.” Iet Systems Biology 1, no. 6 (2007): 313–25. https://doi.org/10.1049/iet-syb:20060063.
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  - Mattingly, J. C., T. M. Suidan, and E. Vanden-Eijnden. “Anomalous dissipation in a stochastically forced infinite-dimensional system of coupled oscillators.” Journal of Statistical Physics 128, no. 5 (2007): 1145–52. https://doi.org/10.1007/s10955-007-9351-8.
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  - Nijhout, H Frederik, Michael C. Reed, David F. Anderson, Jonathan C. Mattingly, S Jill James, and Cornelia M. Ulrich. “Erratum to H. Frederik Nijhout, et al. Epigenetics Volume 1, Issue 2; pp. 81-87..” Epigenetics 1, no. 3 (July 2006): 115–115. https://doi.org/10.4161/epi.1.3.3281.
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  - Hairer, M., and J. C. Mattingly. “Ergodicity of the 2D Navier-Stokes equations with degenerate stochastic forcing.” Annals of Mathematics 164, no. 3 (2006): 993–1032.
  - Mattingly, J. C., and É. Pardoux. “Malliavin calculus for the stochastic 2D Navier-Stokes equation.” Communications on Pure and Applied Mathematics 59, no. 12 (2006): 1742–90. https://doi.org/10.1002/cpa.20136.
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  - Bakhtin, Y., and J. C. Mattingly. “Stationary solutions of stochastic differential equations with memory and stochastic partial differential equations.” Communications in Contemporary Mathematics 7, no. 5 (October 1, 2005): 553–82. https://doi.org/10.1142/S0219199705001878.
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  - Mattingly, J. C., and T. M. Suidan. “The small scales of the stochastic Navier-Stokes equations under rough forcing.” Journal of Statistical Physics 118, no. 1–2 (January 1, 2005): 343–64. https://doi.org/10.1007/s10955-004-8787-3.
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  - Hairer, M., and J. C. Mattingly. “Ergodic properties of highly degenerate 2D stochastic Navier-Stokes equations.” Comptes Rendus Mathematique 339, no. 12 (December 15, 2004): 879–82. https://doi.org/10.1016/j.crma.2004.09.035.
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  - Hairer, M., J. C. Mattingly, and E. Pardoux. “Malliavin calculus for highly degenerate 2D stochastic Navier-Stokes equations.” Comptes Rendus Mathematique 339, no. 11 (December 1, 2004): 793–96. https://doi.org/10.1016/j.crma.2004.09.002.
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  - Hairer, Martin, Jonathan C. Mattingly, and Etienne Pardoux. “Malliavin calculus and ergodic properties of highly degenerate 2D stochastic Navier–Stokes equation.” Arxiv Preprint Math/0409057, 2004.
  - Mattingly, J. C. “Contractivity and ergodicity of the random map x →.” Theory of Probability and Its Applications 47, no. 2 (June 26, 2003): 333–43. https://doi.org/10.1137/S0040585X97979767.
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  - Mattingly, Jonathan C. “On recent progress for the stochastic Navier Stokes equations,” 2003, Exp.No.XI-52.
  - Mattingly, J. C. “The dissipative scale of the stochastics Navier-Stokes equation: Regularization and analyticity.” Journal of Statistical Physics 108, no. 5–6 (December 1, 2002): 1157–79. https://doi.org/10.1023/A:1019799700126.
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  - Mattingly, J. C. “Exponential convergence for the stochastically forced Navier-Stokes equations and other partially dissipative dynamics.” Communications in Mathematical Physics 230, no. 3 (November 1, 2002): 421–62. https://doi.org/10.1007/s00220-002-0688-1.
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  - Mattingly, J. C., A. M. Stuart, and D. J. Higham. “Ergodicity for SDEs and approximations: Locally Lipschitz vector fields and degenerate noise.” Stochastic Processes and Their Applications 101, no. 2 (October 1, 2002): 185–232. https://doi.org/10.1016/S0304-4149(02)00150-3.
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  - Mattingly, J. C., and A. M. Stuart. “Geometric ergodicity of some hypo-elliptic diffusions for particle motions.” Markov Processes and Related Fields 8 (2002): 199–214.
  - Mattingly, Jonathan Christopher. “Contractivity and ergodicity of the random map $x\mapsto|x-\theta|$.” Teoriya Veroyatnostei I Ee Primeneniya 47, no. 2 (2002): 388–97. https://doi.org/10.4213/tvp3671.
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  - Weinan, E., J. C. Mattingly, and Y. Sinai. “Gibbsian dynamics and ergodicity for the stochastically forced Navier-Stokes equation.” Communications in Mathematical Physics 224, no. 1 (December 1, 2001): 83–106. https://doi.org/10.1007/s002201224083.
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  - Weinan, E., and J. C. Mattingly. “Ergodicity for the navier-stokes equation with degenerate random forcing: Finite-dimensional approximation.” Communications on Pure and Applied Mathematics 54, no. 11 (November 1, 2001): 1386–1402. https://doi.org/10.1002/cpa.10007.
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  - Mattingly, J. C. “Ergodicity of 2D Navier-Stokes equations with random forcing and large viscosity.” Communications in Mathematical Physics 206, no. 2 (January 1, 1999): 273–88. https://doi.org/10.1007/s002200050706.
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  - Mattingly, J. C., and Y. G. Sinai. “An elementary proof of the existence and uniqueness theorem for the Navier-Stokes equations.” Communications in Contemporary Mathematics 1, no. 4 (January 1, 1999): 497–516. https://doi.org/10.1142/S0219199799000183.
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  - Holmes, P. J., J. L. Lumley, G. Berkooz, J. C. Mattingly, and R. W. Wittenberg. “Low-dimensional models of coherent structures in turbulence.” Physics Report 287, no. 4 (January 1, 1997): 337–84. https://doi.org/10.1016/S0370-1573(97)00017-3.
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  - Agazzi, Andrea, and Jonathan C. Mattingly. “Seemingly stable chemical kinetics can be stable, marginally stable, or unstable,” n.d.
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  - Bangia, Sachet, Christy Vaughn Graves, Gregory Herschlag, Han Sung Kang, Justin Luo, Jonathan C. Mattingly, and Robert Ravier. “Redistricting: Drawing the Line,” n.d.
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  - Carter, Daniel, Gregory Herschlag, Zach Hunter, and Jonathan Mattingly. “A Merge-Split Proposal for Reversible Monte Carlo Markov Chain Sampling of Redistricting Plans,” n.d.
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  - Carter, Daniel, Zach Hunter, Dan Teague, Gregory Herschlag, and Jonathan Mattingly. “Optimal Legislative County Clustering in North Carolina,” n.d.
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  - Chikina, Maria, Alan Frieze, Jonathan Mattingly, and Wesley Pegden. “Separating effect from significance in Markov chain tests,” n.d.
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  - Gao, Yuan, Kay Kirkpatrick, Jeremy Marzuola, Jonathan Mattingly, and Katherine Newhall. “Limiting Behaviors of High Dimensional Stochastic Spin Ensembles,” n.d.
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  - Herschlag, Gregory, Han Sung Kang, Justin Luo, Christy Vaughn Graves, Sachet Bangia, Robert Ravier, and Jonathan C. Mattingly. “Quantifying Gerrymandering in North Carolina,” n.d.
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  - Heymann, Matthias, Stephen W. Teitsworth, and Jonathan C. Mattingly. “Rare Transition Events in Nonequilibrium Systems with State-Dependent Noise: Application to Stochastic Current Switching in Semiconductor Superlattices,” n.d.
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  - Johndrow, James E., Jonathan C. Mattingly, Sayan Mukherjee, and David Dunson. “Optimal approximating Markov chains for Bayesian inference,” n.d.
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  - Johndrow, James E., and Jonathan C. Mattingly. “Error bounds for Approximations of Markov chains used in Bayesian Sampling,” n.d.
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  - Li, Lei, Jianfeng Lu, Jonathan Mattingly, and Lihan Wang. “Numerical methods for stochastic differential equations based on Gaussian mixture,” n.d.
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  - Lu, Yulong, and Jonathan C. Mattingly. “Geometric ergodicity of Langevin dynamics with Coulomb interactions,” n.d.
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  - Mattingly, Jonathan C., Natesh S. Pillai, and Andrew M. Stuart. “Diffusion limits of the random walk Metropolis algorithm in high dimensions.” Annals of Applied Probability 22, no. 3 (n.d.): 881–930. https://doi.org/10.1214/10-AAP754.
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  - Wang, Chuang, Jonathan Mattingly, and Yue M. Lu. “Scaling Limit: Exact and Tractable Analysis of Online Learning Algorithms with Applications to Regularized Regression and PCA,” n.d.
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- Other Articles
  - Holmes, P. J., J. C. Mattingly, and R. W. Wittenberg. “Low-Dimensional Models of Turbulence.” Springer Netherlands, 2001. https://doi.org/10.1007/978-94-010-0732-0_7.
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- Digital Publications
  - Carter, Daniel, Hunter Zach, Gregory Herschlag, and Jonathan Mattingly. “Optimal Legislative County Clustering in North Carolina,” n.d.
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  - Carter, Daniel, Zach Hunter, Gregory Herschlag, and Jonathan Mattingly. “A Merge-Split Proposal for Reversible Monte Carlo Markov Chain Sampling of Redistricting Plans,” n.d.
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- Conference Papers
  - Mattingly, Jonathan C., and Toufic M. Suidan. “Transition measures for the stochastic Burgers equation,” 409–18. American Mathematical Society, 2008. https://doi.org/10.1090/conm/458/08950.
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Teaching & Mentoring
Recent Courses
- MATH 390: Special Topics in Mathematics 2019
- MATH 493: Research Independent Study 2019
Scholarly, Clinical, & Service Activities
Presentations & Appearances
Outreach & Engaged Scholarship
Service to the Profession

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Education, Training, & Certifications

Duke Appointment History

Academic Positions Outside Duke

In the News

Awards & Honors

Subject Headings

Selected Grants

Selected Publications

Academic Articles

Other Articles

Digital Publications

Conference Papers

Recent Courses

Presentations & Appearances

Outreach & Engaged Scholarship

Service to the Profession