Jonathan Christopher Mattingly
- James B. Duke Distinguished Professor
- Professor of Mathematics
- Chair of the Department of Mathematics
Research Areas and Keywords
Stochastic Analysis, Malliavin Calculus, Ergodic Theory
Stochastic and Random PDEs, Stochastic Dynamical Systems, Mathematical Ecology and Evolution, Metabolic and Cellular modeling, Out of equilibrium statistical mechanics
Markov Chain Mixing, Stochastic Numerical Methods, High Dimensional Random Algorithms
PDE & Dynamical Systems
Stochastic and Random PDEs, Stochastic Dynamical Systems, Malliavin Calculus, Fluid Mechanics, Approximating invariant measures
Stochastic and Random PDEs, Stochastic Dynamical Systems, Fluid Mechanics
Stochastic and Random PDEs, Stochastic Dynamical Systems, Stochastic Analysis, Malliavin Calculus, Markov Chain Mixing, Ergodic Theory, High Dimensional Random Algorithms, Probability on stratified spaces, Out of equilibrium statistical mechanics, Approximating invariant measures
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.
Mattingly, J. C., and E. Pardoux. “Invariant measure selection by noise. An example.” Discrete and Continuous Dynamical Systems Series A, vol. 34, no. 10, Jan. 2014, pp. 4223–57. Scopus, doi:10.3934/dcds.2014.34.4223. Full Text Open Access Copy
Lawley, S. D., et al. “Sensitivity to switching rates in stochastically switched ODEs.” Communications in Mathematical Sciences, vol. 12, no. 7, Jan. 2014, pp. 1343–52. Scopus, doi:10.4310/CMS.2014.v12.n7.a9. Full Text Open Access Copy
Mattingly, J. C., et al. “Geometric ergodicity of a bead-spring pair with stochastic Stokes forcing.” Stochastic Processes and Their Applications, vol. 122, no. 12, Dec. 2012, pp. 3953–79. Scopus, doi:10.1016/j.spa.2012.07.003. Full Text Open Access Copy
Luo, Shishi, et al. “The impact of host immune status on the within-host and population dynamics of antigenic immune escape.” J R Soc Interface, vol. 9, no. 75, Oct. 2012, pp. 2603–13. Pubmed, doi:10.1098/rsif.2012.0180. Full Text Open Access Copy
Athreyaz, A., et al. “Propagating lyapunov functions to prove noise-induced stabilization.” Electronic Journal of Probability, vol. 17, 2012. Scival, doi:10.1214/EJP.v17-2410. Full Text Open Access Copy
Porporato, A., et al. “Local kinetic interpretation of entropy production through reversed diffusion.” Phys Rev E Stat Nonlin Soft Matter Phys, vol. 84, no. 4 Pt 1, Oct. 2011, p. 041142. Pubmed, doi:10.1103/PhysRevE.84.041142. Full Text Open Access Copy
Hairer, Martin, and Jonathan C. Mattingly. Yet Another Look at Harris’ Ergodic Theorem for Markov Chains. Springer Basel, 2011, pp. 109–17. Crossref, doi:10.1007/978-3-0348-0021-1_7. Full Text Open Access Copy
Hairer, M., et al. “Asymptotic coupling and a general form of Harris' theorem with applications to stochastic delay equations.” Probability Theory and Related Fields, vol. 149, no. 1, 2011, pp. 223–59. Scival, doi:10.1007/s00440-009-0250-6. Full Text Open Access Copy