Jonathan Christopher Mattingly
Kimberly J. Jenkins Distinguished University Professor of New Technologies
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.
Since 2013 he has also been working to understand and quantify gerrymandering and its interaction of a region's geopolitical landscape. This has lead him to testify in a number of court cases including in North Carolina, which led to the NC congressional and both NC legislative maps being deemed unconstitutional and replaced for the 2020 elections.
He is the recipient of a Sloan Fellowship and a PECASE CAREER award. He is also a fellow of the IMS and the AMS. He was awarded the Defender of Freedom award by Common Cause for his work on Quantifying Gerrymandering.
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.
Since 2013 he has also been working to understand and quantify gerrymandering and its interaction of a region's geopolitical landscape. This has lead him to testify in a number of court cases including in North Carolina, which led to the NC congressional and both NC legislative maps being deemed unconstitutional and replaced for the 2020 elections.
He is the recipient of a Sloan Fellowship and a PECASE CAREER award. He is also a fellow of the IMS and the AMS. He was awarded the Defender of Freedom award by Common Cause for his work on Quantifying Gerrymandering.
Current Appointments & Affiliations
- Kimberly J. Jenkins Distinguished University Professor of New Technologies, Mathematics, Trinity College of Arts & Sciences 2022
- Professor of Mathematics, Mathematics, Trinity College of Arts & Sciences 2012
- Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2016
Contact Information
- 120 Science Drive, I, Durham, NC 27708
- 297 Physics Building, Box 90320, Durham, NC 27708
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jonathan.mattingly@duke.edu
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#Personal Website
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Arxiv Page
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Google Scholar Page
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Quantifying Gerrymandering : A nonpartisan research group centered @ Duke Math
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Stochastically Yours
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The Probability Workbook
- Background
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Education, Training, & Certifications
- Ph.D., Princeton University 1998
- M.A., Princeton University 1996
- B.S., Yale University 1992
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Previous Appointments & Affiliations
- James B. Duke Distinguished Professor, Mathematics, Trinity College of Arts & Sciences 2019 - 2022
- Chair of the Department of Mathematics, Mathematics, Trinity College of Arts & Sciences 2016 - 2020
- 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
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Academic Positions Outside Duke
- Member, Institute for advanced study. 2021
- 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
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In the News
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MAR 13, 2023 Duke Today -
DEC 10, 2021 -
NOV 3, 2021 -
OCT 1, 2021 -
MAY 7, 2019 -
MAR 25, 2019 -
MAR 14, 2019 -
JUL 2, 2018 SIAM News -
JUN 26, 2018 PANS News -
JAN 21, 2018 City Lab -
JAN 18, 2018 Valley News -
JAN 18, 2018 Nature News -
JAN 11, 2018 Durham Harold Sun -
JAN 8, 2018 Duke Research Blog -
OCT 6, 2017 NY Times -
JUN 1, 2017 Nature News -
NOV 28, 2016 -
MAR 18, 2015 USA Today -
MAR 18, 2015 Chicago Sun-Times -
MAR 17, 2015 -
MAR 17, 2015 -
DEC 5, 2014 The Atlantic -
NOV 26, 2014 WUNC -
NOV 12, 2014 Greensboro News & Record -
OCT 30, 2014 WFAE-Charlotte -
OCT 30, 2014 -
OCT 29, 2014
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Awards & Honors
- IE Block Community Lecture. SIAM. July 2021
- School of Mathematics/ Member. Institute for Advanced Study. 2021
- Defenders of Democracy. National Common Cause. 2018
- Fellow of the American Mathematical Society . American Mathematical Society. 2015
- Simons Visiting Professor . MSRI. 2015
- Institute of Mathematical Statistics Fellow. Institute of Mathematical Statistics. June 2012
- Faculty Early Career Development (CAREER) Program. National Science Foundation. 2005
- Presidential Early Career Awards for Scientists and Engineers. National Science Foundation. 2005
- Sloan Research Fellowship-Mathematics. Alfred P. Sloan Foundation. 2005
- School of Mathematics/ Members. Institute for Advanced Study. 2002
- Expertise
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Subject Headings
- Differential equations, Nonlinear
- Ergodic theory
- Evolution
- Fluid mechanics
- Folic Acid
- Invariant measures
- Lyapunov functions
- Malliavin calculus
- Mixing
- Models, Biological
- Nonequilibrium statistical mechanics
- Nonlinear Dynamics
- Probability Theory
- Random dynamical systems
- Stochastic Processes
- Stochastic analysis
- Stochastic differential equations
- Stochastic partial differential equations
- Turbulence
- Research
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Selected Grants
- RTG: Training Tomorrow's Workforce in Analysis and Applications awarded by National Science Foundation 2021 - 2026
- Quantifying Gerrymandering in the North Carolina Legislature awarded by Imagine North Carolina First 2022 - 2025
- HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms awarded by National Science Foundation 2019 - 2023
- Collaborative research: Propagation of dissipation: Stochastic stabilization in finite and infinite dimensions awarded by National Science Foundation 2016 - 2021
- BIGDATA:F: Scalable Bayes uncertainty quantification with guarantees awarded by National Science Foundation 2015 - 2020
- Quantifying Gerrymandering in the North Carolina Legislature awarded by Imagine North Carolina First 2019
- Analysis and design of robust rare event simulation methods for protein folding and disease related aggregation 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: Enhanced Training and Recruitment in Mathematical Biology awarded by National Science Foundation 2010 - 2017
- Multiscale Analysis of Dynamic Graphs awarded by Office of Naval Research 2012 - 2016
- FRG: Collaborative Proposal: Stochastics and Dynamics: Asymptotic Problems 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
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External Relationships
- ACLU
- Brown University
- Brown University/ ICERM
- Common Cause
- SIAM
- Southern Coalition for Social Justice
- The Arnold and Porter Law Firm
- Publications & Artistic Works
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Selected Publications
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Academic Articles
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Agazzi, A., J. C. Mattingly, and O. Melikechi. “Random Splitting of Fluid Models: Unique Ergodicity and Convergence.” Communications in Mathematical Physics, January 1, 2023. https://doi.org/10.1007/s00220-023-04645-5.Full Text
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Herzog, D. P., J. C. Mattingly, and H. D. Nguyen. “Gibbsian dynamics and the generalized Langevin equation.” Electronic Journal of Probability 28 (January 1, 2023). https://doi.org/10.1214/23-EJP904.Full Text
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Mattingly, J. C., M. Romito, and L. Su. “The Gaussian structure of the singular stochastic Burgers equation.” Forum of Mathematics, Sigma 10 (September 2, 2022). https://doi.org/10.1017/fms.2022.64.Full Text Open Access Copy
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Earle, Gabriel, and Jonathan Mattingly. “Convergence of Stratified MCMC Sampling of Non-Reversible Dynamics,” November 10, 2021.Open Access Copy Link to Item
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Herzog, David P., Jonathan C. Mattingly, and Hung D. Nguyen. “Gibbsian dynamics and the generalized Langevin equation,” November 7, 2021.Open Access Copy Link to Item
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Gao, Y., K. Kirkpatrick, J. Marzuola, J. Mattingly, and K. A. Newhall. “LIMITING BEHAVIORS OF HIGH DIMENSIONAL STOCHASTIC SPIN ENSEMBLES*.” Communications in Mathematical Sciences 19, no. 2 (January 1, 2021): 453–94. https://doi.org/10.4310/CMS.2021.v19.n2.a7.Full Text Open Access Copy
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Autry, E. A., D. Carter, G. J. Herschlag, Z. Hunter, and J. C. Mattingly. “METROPOLIZED MULTISCALE FOREST RECOMBINATION for REDISTRICTING.” Multiscale Modeling and Simulation 19, no. 4 (January 1, 2021): 1885–1914. https://doi.org/10.1137/21M1406854.Full Text Open Access Copy
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Bakhtin, Y., T. Hurth, S. D. Lawley, and J. C. Mattingly. “Singularities of invariant densities for random switching between two linear ODEs in 2D.” Siam Journal on Applied Dynamical Systems 20, no. 4 (January 1, 2021): 1917–58. https://doi.org/10.1137/20M1364345.Full Text Open Access Copy
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Li, L., J. Lu, J. C. Mattingly, and L. Wang. “Numerical Methods For Stochastic Differential Equations Based On Gaussian Mixture.” Communications in Mathematical Sciences 19, no. 6 (January 1, 2021): 1549–77. https://doi.org/10.4310/CMS.2021.v19.n6.a5.Full Text Open Access Copy
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Gao, Y., J. L. Marzuola, J. C. Mattingly, and K. A. Newhall. “Nonlocal stochastic-partial-differential-equation limits of spatially correlated noise-driven spin systems derived to sample a canonical distribution.” Physical Review E 102, no. 5 (November 9, 2020). https://doi.org/10.1103/PhysRevE.102.052112.Full Text Open Access Copy
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Gao, Yuan, Jeremy L. Marzuola, Jonathan C. Mattingly, and Katherine A. Newhall. “Nonlocal stochastic-partial-differential-equation limits of spatially correlated noise-driven spin systems derived to sample a canonical distribution.” Physical Review. E 102, no. 5–1 (November 2020): 052112. https://doi.org/10.1103/physreve.102.052112.Full Text Open Access Copy
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Leimbach, Matti, Jonathan C. Mattingly, and Michael Scheutzow. “Noise-induced strong stabilization,” September 22, 2020.Open Access Copy Link to Item
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Autry, Eric A., Daniel Carter, Gregory Herschlag, Zach Hunter, and Jonathan C. Mattingly. “Multi-Scale Merge-Split Markov Chain Monte Carlo for Redistricting,” August 18, 2020.Open Access Copy Link to Item
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Herschlag, Gregory, Jonathan C. Mattingly, Matthias Sachs, and Evan Wyse. “Non-reversible Markov chain Monte Carlo for sampling of districting maps,” August 18, 2020.Open Access Copy Link to Item
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AGAZZI, A., and J. C. MATTINGLY. “SEEMINGLY STABLE CHEMICAL KINETICS CAN BE STABLE, MARGINALLY STABLE, OR UNSTABLE.” Communications in Mathematical Sciences 18, no. 6 (January 1, 2020): 1605–42. https://doi.org/10.4310/CMS.2020.v18.n6.a5.Full Text Open Access Copy
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Chikina, M., A. Frieze, J. C. Mattingly, and W. Pegden. “Separating Effect From Significance in Markov Chain Tests.” Statistics and Public Policy 7, no. 1 (January 1, 2020): 101–14. https://doi.org/10.1080/2330443X.2020.1806763.Full Text Open Access Copy
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Lu, Y., and J. C. Mattingly. “Geometric ergodicity of Langevin dynamics with Coulomb interactions.” Nonlinearity 33, no. 2 (January 1, 2020): 675–99. https://doi.org/10.1088/1361-6544/ab514a.Full Text Open Access Copy
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Carter, D., Z. Hunter, D. Teague, G. Herschlag, and J. Mattingly. “Optimal Legislative County Clustering in North Carolina.” Statistics and Public Policy 7, no. 1 (January 1, 2020): 19–29. https://doi.org/10.1080/2330443X.2020.1748552.Full Text Open Access Copy
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Herschlag, G., H. S. Kang, J. Luo, C. V. Graves, S. Bangia, R. Ravier, and J. C. Mattingly. “Quantifying Gerrymandering in North Carolina.” Statistics and Public Policy 7, no. 1 (January 1, 2020): 30–38. https://doi.org/10.1080/2330443X.2020.1796400.Full Text Open Access Copy
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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.Full Text Open Access Copy Link to Item
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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).Open Access Copy
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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,” December 7, 2017.Open Access Copy Link to Item
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Johndrow, James E., and Jonathan C. Mattingly. “Error bounds for Approximations of Markov chains used in Bayesian Sampling,” November 14, 2017.Open Access Copy Link to Item
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Herschlag, G., R. Ravier, and J. C. Mattingly. “Evaluating Partisan Gerrymandering in Wisconsin,” September 2, 2017.Open Access Copy Link to Item
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Bakhtin, Y., T. Hurth, S. D. Lawley, and J. C. Mattingly. “Smooth invariant densities for random switching on the torus (Submitted),” August 1, 2017.Open Access Copy Link to Item
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Johndrow, J. E., and J. C. Mattingly. “Coupling and Decoupling to bound an approximating Markov Chain (Submitted),” July 31, 2017.Open Access Copy Link to Item
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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 (Accepted).” Annals of Pde, June 30, 2017.Open Access Copy Link to Item
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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,” April 9, 2017.Open Access Copy Link to Item
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Hairer, M., and J. Mattingly. “The strong Feller property for singular stochastic PDEs (Submitted),” 2016.Open Access Copy Link to Item
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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 (Accepted).” Siam Review, 2016.Open Access Copy Link to Item
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Johndrow, James E., Jonathan C. Mattingly, Sayan Mukherjee, and David Dunson. “Optimal approximating Markov chains for Bayesian inference,” August 13, 2015.Open Access Copy Link to Item
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Glatt-Holtz, N., G. Richards, and J. C. Mattingly. “On Unique Ergodicity in Nonlinear Stochastic Partial Differential Equations (Submitted),” 2015.Open Access Copy Link to Item
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Luo, S., and J. C. Mattingly. “Scaling limits of a model for selection at two scales,” 2015.Open Access Copy Link to Item
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Huckemann, Stephan, Jonathan C. Mattingly, Ezra Miller, and James Nolen. “Sticky central limit theorems at isolated hyperbolic planar singularities.” Electronic Journal of Probability 20 (2015): 1–34. https://doi.org/10.1214/EJP.v20-3887.Full Text Open Access Copy
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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.Full Text Open Access Copy
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Herzog, David P., and Jonathan Christopher Mattingly. “Noise-Induced Stabilization of Planar Flows II,” April 2014.Open Access Copy
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Bakhtin, Yuri, Tobias Hurth, and Jonathan C. Mattingly. “Regularity of invariant densities for 1D-systems with random switching.” Arxiv Preprint Arxiv:1406.5425, 2014.Open Access Copy
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Herzog, David P., and Jonathan C. Mattingly. “Noise-Induced Stabilization of Planar Flows I.” Arxiv Preprint Arxiv:1404.0957, 2014.Open Access Copy
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Herzog, David P., and Jonathan C. Mattingly. “A practical criterion for positivity of transition densities.” Arxiv Preprint Arxiv:1407.3858, 2014.Open Access Copy
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Mattingly, Jonathan C., and Christy Vaughn. “Redistricting and the Will of the People.” Arxiv Preprint Arxiv:1410.8796, 2014.Open Access Copy
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Mattingly, Jonathan C., and Etienne Pardoux. “Invariant measure selection by noise. An example.” Discrete and Continuous Dynamical Systems. Series A 34 (2014): 4223–57. https://doi.org/10.3934/dcds.2014.34.4223.Full Text Open Access Copy
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Lawley, Sean D., Jonathan C. Mattingly, and Michael C. Reed. “Sensitivity to switching rates in stochastically switched ODEs.” Communications in Mathematical Sciences 12 (2014): 1343–52. https://doi.org/10.4310/CMS.2014.v12.n7.a9.Full Text Open Access Copy
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Lawley, Sean D., Jonathan C. Mattingly, and Michael C. Reed. “Stochastic switching in infinite dimensions with applications to random parabolic PDEs.” Arxiv Preprint Arxiv:1407.2264, 2014.Open Access Copy
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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.Full Text Open Access Copy
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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.Full Text Open Access Copy
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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.Full Text Open Access Copy Link to Item
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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.Full Text Open Access Copy
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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): 041142. https://doi.org/10.1103/PhysRevE.84.041142.Full Text Open Access Copy Link to Item
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Cooke, Ben, Jonathan C. Mattingly, Scott A. McKinley, and Scott C. Schmidler. “Geometric Ergodicity of Two–dimensional Hamiltonian systems with a Lennard–Jones–like Repulsive Potential.” Arxiv Preprint Arxiv:1104.3842, 2011.Open Access Copy
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Hairer, Martin, and Jonathan C. Mattingly. “Yet another look at Harris’ ergodic theorem for Markov chains” 63 (2011): 109–17. https://doi.org/10.1007/978-3-0348-0021-1_7.Full Text Open Access Copy
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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.Open Access Copy
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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.Full Text Open Access Copy
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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.Open Access Copy
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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.Full Text Open Access Copy
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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,” August 24, 2010.Open Access Copy Link to Item
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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 (March 22, 2010): 881–930.Open Access Copy Link to Item
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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.Full Text Open Access Copy
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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.Full Text Open Access Copy
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Iyer, Gautam, and Jonathan Mattingly. “A stochastic-Lagrangian particle system for the Navier-Stokes equations.” Nonlinearity 21 (2008): 2537–53. https://doi.org/10.1088/0951-7715/21/11/004.Full Text Open Access Copy
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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.Open Access Copy
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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 (November 2007): 313–25. https://doi.org/10.1049/iet-syb:20060063.Full Text
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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.Full Text Open Access Copy
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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.Full Text
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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.Full Text Open Access Copy
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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 (January 1, 2007): 479–506. https://doi.org/10.1093/imanum/drl032.Full Text Open Access Copy
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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.Full Text Open Access Copy
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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.Full Text
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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.
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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.Full Text Open Access Copy
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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.Full Text Open Access Copy
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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.Full Text
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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.
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Hairer, Martin, Jonathan C. Mattingly, and Étienne Pardoux. “Malliavin calculus for highly degenerate 2D stochastic Navier-Stokes equations.” Comptes Rendus Mathématique. Académie Des Sciences. Paris 339 (2004): 793–96. https://doi.org/10.1016/j.crma.2004.09.002.Full Text
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Hairer, Martin, and Jonathan C. Mattingly. “Ergodic properties of highly degenerate 2D stochastic Navier-Stokes equations.” Comptes Rendus Mathématique. Académie Des Sciences. Paris 339 (2004): 879–82. https://doi.org/10.1016/j.crma.2004.09.035.Full Text Open Access Copy
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Mattingly, Jonathan C. “On recent progress for the stochastic Navier Stokes equations,” 2003, Exp.No.XI-52.
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Mattingly, J. C. “Contractivity and ergodicity of the random map $x\mapsto\vert x-θ\vert $.” Rossi\U\I Skaya Akademiya Nauk. Teoriya Veroyatnoste\U\I I Ee Primeneniya 47 (2002): 388–97. https://doi.org/10.1137/S0040585X97979767.Full Text Open Access Copy
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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 (2002): 185–232. https://doi.org/10.1016/S0304-4149(02)00150-3.Full Text
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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.
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Mattingly, Jonathan C. “The dissipative scale of the stochastics Navier-Stokes equation: regularization and analyticity.” Journal of Statistical Physics 108 (2002): 1157–79. https://doi.org/10.1023/A:1019799700126.Full Text
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Mattingly, Jonathan C. “Exponential convergence for the stochastically forced Navier-Stokes equations and other partially dissipative dynamics.” Communications in Mathematical Physics 230 (2002): 421–62. https://doi.org/10.1007/s00220-002-0688-1.Full Text
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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.Full Text Open Access Copy
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E, Weinan, J. C. Mattingly, and Ya Sinai. “Gibbsian dynamics and ergodicity for the stochastically forced Navier-Stokes equation.” Communications in Mathematical Physics 224 (2001): 83–106. https://doi.org/10.1007/s002201224083.Full Text
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E, Weinan, and Jonathan C. Mattingly. “Ergodicity for the Navier-Stokes equation with degenerate random forcing: finite-dimensional approximation.” Communications on Pure and Applied Mathematics 54 (2001): 1386–1402. https://doi.org/10.1002/cpa.10007.Full Text Open Access Copy
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Mattingly, J. C., and Ya G. Sinai. “An elementary proof of the existence and uniqueness theorem for the Navier-Stokes equations.” Communications in Contemporary Mathematics 1 (1999): 497–516. https://doi.org/10.1142/S0219199799000183.Full Text Open Access Copy
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Mattingly, Jonathan C. “Ergodicity of $2$D Navier-Stokes equations with random forcing and large viscosity.” Communications in Mathematical Physics 206 (1999): 273–88. https://doi.org/10.1007/s002200050706.Full Text
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Holmes, Philip J., John L. Lumley, Gal Berkooz, Jonathan C. Mattingly, and Ralf W. Wittenberg. “Low-dimensional models of coherent structures in turbulence.” Physics Reports. a Review Section of Physics Letters 287 (1997): 337–84. https://doi.org/10.1016/S0370-1573(97)00017-3.Full Text
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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.Open Access Copy Link to Item
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Book Sections
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Hairer, M., and J. C. Mattingly. “Yet Another Look at Harris’ Ergodic Theorem for Markov Chains.” In Progress in Probability, 63:109–17, 2011. https://doi.org/10.1007/978-3-0348-0021-1_7.Full Text
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Other Articles
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Holmes, P. J., J. C. Mattingly, and R. W. Wittenberg. “Low-dimensional models of turbulence or, The dynamics of coherent structures.” Kluwer Acad. Publ., Dordrecht, 2001. https://doi.org/10.1007/978-94-010-0732-0_7.Full Text
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Digital Publications
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Carter, Daniel, Hunter Zach, Gregory Herschlag, and Jonathan Mattingly. “Optimal Legislative County Clustering in North Carolina (Submitted),” November 22, 2019.Open Access Copy Link to Item
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Reports
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Mattingly, Jonathan. “Expert Report on the North Carolina State Legislature and Congressional Redistricting in Harper v Hall/Moore,” December 23, 2021.Open Access Copy
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Mattingly, Jonathan. “Rebuttal Of Defendant’s Expert Reports For Common Cause V. Lewis,” June 2019.Open Access Copy
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Mattingly, Jonathan. “Expert Report on the North Carolina State Legislature in Harper v. Lewis,” April 2019.Open Access Copy
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Mattingly, Jonathan. “Expert report in Common Cause v Rucho,” March 6, 2017.Open Access Copy
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Conference Papers
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Zhao, Z., C. Hettle, S. Gupta, J. C. Mattingly, D. Randall, and G. J. Herschlag. “Mathematically Quantifying Non-responsiveness of the 2021 Georgia Congressional Districting Plan.” In Acm International Conference Proceeding Series, 2022. https://doi.org/10.1145/3551624.3555300.Full Text
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Mattingly, Jonathan C., and Toufic M. Suidan. “Transition measures for the stochastic Burgers equation,” 458:409–18. Amer. Math. Soc., Providence, RI, 2008. https://doi.org/10.1090/conm/458/08950.Full Text Open Access Copy
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Theses and Dissertations
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Mattingly, Jonathan. “The Stochastic Navier-Stokes Equation: Energy Estimates and Phase Space Contraction.” Edited by Yakov Sinai, n.d.Open Access Copy
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Preprints
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Elgindi, Tarek M., Kyle Liss, and Jonathan C. Mattingly. “Optimal enhanced dissipation and mixing for a time-periodic, Lipschitz velocity field on $\mathbb{T}^2$,” April 11, 2023.Link to Item
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Agazzi, Andrea, Jonathan C. Mattingly, and Omar Melikechi. “Random Splitting of Fluid Models: Positive Lyapunov Exponents,” October 6, 2022.Open Access Copy Link to Item
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Zhao, Zhanzhan, Cyrus Hettle, Swati Gupta, Jonathan Mattingly, Dana Randall, and Gregory Herschlag. “Mathematically Quantifying Non-responsiveness of the 2021 Georgia Congressional Districting Plan,” March 12, 2022.Open Access Copy Link to Item
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Agazzi, Andrea, Jonathan C. Mattingly, and Omar Melikechi. “Random Splitting of Fluid Models: Ergodicity and Convergence,” January 17, 2022.Open Access Copy Link to Item
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- Teaching & Mentoring
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Recent Courses
- MATH 545: Introduction to Stochastic Calculus 2023
- MATH 790-90: Minicourse in Advanced Topics 2023
- MATH 230: Probability 2022
- MATH 451S: Nonlinear Dynamics and Chaos 2022
- MATH 730: Probability 2022
- MATH 751S: Nonlinear Ordinary Differential Equations 2022
- MATH 895: Internship 2022
- STA 230: Probability 2022
- MATH 545: Introduction to Stochastic Calculus 2021
- Scholarly, Clinical, & Service Activities
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Presentations & Appearances
- A randomly split model for Euler Dynamics. Stochastic PDEs and Related Topics. Brin Mathematics Reseawrch Center. October 2022 2022
- A model for random Euler and Navier Stokes equations based on a randomized splitting of the dynamics.. Small Scale Dynamics in Fluid Motion. Simons Center for Geometry and Physics. June 13, 2022 - June 24, 2022 2022
- Random Splitting for Euler's equations. Mathematical physics at coffee, the first 50 years. University of Geneva. June 2022 2022
- Thinking about Erodidicy of SPDEs. Unifying concepts in PDEs with randomness. Centre de Rechearch Menthematique. May 16, 2022 - May 27, 2022 2022
- Using Computational Sampling to Quantify Gerrymandering. Boeing Seminar. Applied MAth. March 10, 2022 2022
- A new model of randomly forced Fluid equations. Members seminar. IAS. December 2021 2021
- The Mathematics and Policy of Gerrymandering. IAS. December 2021 2021
- A new model of randomly forced Fluid equations. Princeton Fluids Seminar. November 2021 2021
- Barton Lectures in Computational Mathematics. UNCG. November 2021 2021
- A new model of randomly forced Fluid equations. Conference on Wave Turbulence. ICEM. October 2021 2021
- Panel on Qunatifying Gerrymandering. Redistricting and American Democracy . Democracy in America. October 2021 2021
- Hearing the Will of the People. Joint Stats Meeting. ISM. August 2021 2021
- Non-reversible samplers for Gerrymandering. Non reversible MCMC. August 2021 2021
- IE Block Community Lecture . SIAM. July 2021 2021
- The Gaussian Structure of the Stochastically Forced Burgers Equation. SPDE & Friends. May 2021 2021
- Gaussian Structure of Stochastic Burgers. Wave Turbulence online seminar. February 2021 2021
- Gaussian Structure of Burgers Equation. January 2021 2021
- Sampling to Understand Gerrymandering and Influence Public Policy. Policymaking in Operations Research . MIT. January 2021 2021
- New Sampling Methods of Quantifying Gerrymandering . Brown Applied Math Colloquium . October 2020 2020
- Quantifying and Understanding Gerrymandering - How a quest to understand his state's political geography led a mathematician to court. Public Lecture. ICERM . October 2020 2020
- New Sampling Methods to Quantify Gerymandering. Redistricting Conference 2020. Duke Law and TRIPODS. March 2020 2020
- Quantifying Gerrymandering Using Sampling. AAAS. January 2020 2020
- AMS Regional Meeting Plenary Speaker. AMS. 2019 2019
- Long Time Numerical Simulation of SDEs. SciCADE2019 . 2019 2019
- Interactions between noise and instabilities.. Stochastic Dynamics Out of Equilibrium. IHP, Paris. July 2018 2018
- Quantifying Gerrymandering: A Mathematician Goes to Court. PCMI Public Lecture. July 2018 2018
- Anatomy of an ergodic theorem. Recent trends in continuous and discrete . June 2018 - June 2018 2018
- Approximate/exact controllability and ergodicity for (additive noise) SPDEs/SODEs. Stochastic Partial Differential Equations. CIRM, Marseilles . May 2018 2018
- Discovering the geopolitical structure of the United States through Markov Chain Monte Carlo sampling. Data driven modelling of complex systems. The Alan Turing Institute, UK. May 2018 2018
- Ergodicity of Singular SPDEs. Transport and localization in random media: theory and applications. May 2018 2018
- Quantifying Gerrymandering: A mathematician goes to court. 2018 Niven Lecture. UBC. May 2018 2018
- Drawing the line in redistricting (A mathematician's take). Institute for International Studies. Stanford University. March 2018 2018
- Ergodic and global solutions for singular SPDEs. FRONTIER PROBABILITY DAYS. March 2018 2018
- Quantifying Gerrymandering: a mathematician goes to court. de Leeuw Distinguished Lecture Series . Stanford Mathematics Department. March 2018 2018
- A mathematician Goes to Court. 2017 Fields Medal Symposium. October 2017 2017
- Stabilization of Stochastic Dynamics . Turbulence, Mixing and stability. IPAM. January 2017 2017
- Stochastic PDEs. Gene Golub SIAM Summer School. July 2016 - August 2016 2016
- Stabilization and noise. Department Colloquium. Berekey Mathematics Department. November 12, 2015 2015
- Stochastic PDEs. Analysis of PDEs of Fluid Mechanics. October 2015 2015
- Ergodicity Finite and Infinite dimentional Markov Chains. CRM-PIMS Summer School in Probability. McGill University. July 2015 2015
- Dynamics Days 2014. January 4, 2014 2014
- Stabilization by Noise. November 19, 2013 2013
- Uniqueness of the inviscid limit in a simple model damped/driven system.. November 5, 2013 2013
- Stochastic stabilization of OEDs.. September 6, 2013 2013
- Stochastic partial differential equations. August 1, 2013 2013
- Stabilization by noise. May 1, 2013 2013
- Stablization by Noise. February 14, 2013 2013
- Perspectives on Ergodicity. January 14, 2013 2013
- A Numerical Method for the SDEs from Chemical Equations. December 1, 2012 2012
- Minerva Lectures: Erodicity of Markov Processes: From Chains to SDEs to SPDEs. November 1, 2012 2012
- A Menagerie of Stabilization. July 1, 2012 2012
- Stochastic Stabilization. July 1, 2012 2012
- Building Lyapunov Functions (4 lectures). March 1, 2012 2012
- Noise Induced Stability. February 1, 2012 2012
- A Menagerie of Stochastic Stabilization. October 18, 2011 2011
- A menagerie of stochastic stabilization. August 1, 2011 2011
- Coarse–graining of many–body systems: analysis, computations and applications. July 1, 2011 2011
- Ergodicity of systems with singular interaction terms. November 18, 2010 2010
- Oberwolfach Seminar: The Ergodic Theory of Markov Processes. October 1, 2010 2010
- Malliavin Calculus to prove ergodic theorems for SPDEs. August 13, 2010 2010
- SPDE scaling limits of an Markov chain Montecarlo algorithm. June 28, 2010 2010
- The spread of randomness. June 1, 2010 2010
- How to prove an ergodic theorem. May 1, 2010 2010
- Coupling at infinity. March 30, 2010 2010
- Long time stochastic simiulation. March 15, 2010 2010
- Spectral Gaps in Wasserstien Distance. March 4, 2010 2010
- Trouble with a chain of stochastic oscillators. March 2, 2010 2010
- Hypo-ellipticity for SPDEs. March 1, 2010 2010
- Numerics of SDEs. February 24, 2010 2010
- Long Time Behavior of Stochastically Forced PDEs.. January 14, 2010 2010
- Ellipticity and Hypo-ellipticity for SPDEs *or* What is ellipticity in infinite dimensions anyway?. January 8, 2010 2010
- SPDE Limits of the Random Walk Metropolis Algorithm in High Dimensions. December 7, 2009 2009
- Stochastic fluctuations in bio chemical networks. November 9, 2009 2009
- Introduction to Ergodicity in Infinite Dimentions. July 1, 2009 2009
- What makes infinite dimensional Markov processes different ?. July 1, 2009 2009
- Stochastically forced fluid equations: Transfer between scales and ergodicity.. April 4, 2009 2009
- Trouble with a chain of stochastic oscillators. PACM. April 3, 2009 2009
- What makes the ergodic theory if Markov Chains in infinite dimensions different (and dificult) ?. March 3, 2009 2009
- Ergodicity, Energy Transfer, and Stochastic Partial Differential Equations. Columbia University. December 15, 2008 2008
- The Spread of Randomness: Ergodicity in Infinite Dimensions. December 15, 2008 2008
- The spread of randomness through dimensions. November 1, 2008 2008
- The spread of randomness through dimensions. November 1, 2008 2008
- Troubles with oscillators. October 1, 2008 2008
- What is different about the ergodic theory of stochastic PDEs (vs ODEs). October 1, 2008 2008
- Trouble with a chain of stochastic oscillators. September 1, 2008 2008
- Troubles with oscillators. August 1, 2008 2008
- The spread of randomness in infinite dimensions and ergodicity for SPDEs. June 1, 2008 2008
- Troubles with chains of anharmonic oscillators. June 1, 2008 2008
- Ergodicity of Degenerately forced SPDEs. May 27, 2008 2008
- Ergodicity of Degenerately forced SPDEs. May 1, 2008 2008
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Outreach & Engaged Scholarship
- Data+ Project Leader. Data+. 2021 - 2022 2021 - 2022
- Bass Connections Faculty Team Leader. Gerrymandering and the Extent of Democracy in America. 2018 - 2019 2018 - 2019
- Bass Connections Faculty Team Leader. Data+ Project Lead. 2017 2017
- Bass Connections Faculty Team Member. Data+. June 2016 - July 2016 2016
- Bass Connections Faculty Team Member . Data+. June 2015 - August 2016 2015 - 2016
- Organizer . Discovering Research in Mathematics. 2011 - 2018 2011 - 2018
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Service to the Profession
- Co-organizer . Algorithms, Fairness, and Equity Program. MSRI/SLMath. August 2023 - December 2023 2023
- Organizing Committee. SIAM online PDE seminar. SIAM. 2022 - 2022 2022
- Scientific Advisory Committee . Pacific Institute of Mathemtical Scineces. 2022 - 2025 2022 - 2025
- Participant. Faculty Curriculum on Anti-Racism. Duke Office of Faculty Advancement. January 11, 2021 - January 14, 2021 2021
- Committee to Select the Gibbs Lecturer for 2020 and 2021. AMS. February 2019 - January 2021 2019 - 2021
- Co-Organizer . Quantifying Gerrymandering. SAMSI. October 2018 2018
- Co-Organizer . Regional Gerrymandering Conference. November 2017 2017
- Co-Organizer . Interacting particle systems WITH APPLICATIONS IN BIOLOGY, ECOLOGY, AND STATISTICAL PHYSICS. SEPC 2017. May 2017 2017
- Board of Trustees . ICERM. NSF Math Institute . 2017 - 2021 2017 - 2021
- Organiser Special Term. MSRI, Berkeley CA. August 2015 - December 2015 2015
- Associate editor Nonlinearity. December 2013 2013
- Organized invited session at SPA2013. August 2013 2013
- Co Organizer (with Amarjit Budhiraja ) : Seminar on Stochastic Processes 2013. March 2013 2013
- Local Orgnaizer (with Rick Durrett) : Woman in Probability III. October 2012 2012
- Associate Editor : Journal of Stochastic Partial Differential Equations. September 2012 2012
- SAMSI Stochastic Dynamics tradition workshop. November 2010 2010
- MFO week long school on ergodic theory. October 2010 2010
- SAMSI Opening Workshop for Stochastic Dynamics. August 2009 2009
- AMS Short Course Selelction Committee. 2009 - 2011 2009 - 2011
- Scientific Advisory Committee . NimBios, NSF Math/Bio center. 2009 - 2012 2009 - 2012
- local liaison/Organizer SAMSI year on stochastic dynamics. 2009 - 2010 2009 - 2010
- Committee on Commitees. AMS. 2008 - 2009 2008 - 2009
- Organiser Special Term. MSRI, Berkeley CA. August 2007 - December 2007 2007
Some information on this profile has been compiled automatically from Duke databases and external sources. (Our About page explains how this works.) If you see a problem with the information, please write to Scholars@Duke and let us know. We will reply promptly.