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Publications
  1. L. S. Meissner, A. Frommer, K. Kahl, and J. B. Schroder, Stochastic Multilevel Trace Estimation for the Kirchhoff Index. Advances in Computational Mathematics, Springer. Submitted March 2026.
  2. R. Yoda, E. C. Cyr, J. B. Schroder, M. Bolten, and S. Friedhoff, Toward Seamless Integration of Layer-Parallel Training via Multigrid-in-Time for Deep Neural Networks. JSIAM Letters, Japan Society for Industrial and Applied Mathematics. Submitted March 2025.
  3. S. Jiang, M. Salvado, E. C. Cyr, A. Kopanicakova, R. Krause, and J. B. Schroder, Layer-Parallel Training for Transformers. Springer Proceedings in Mathematics and Statistics, Go20 CSCS, Malta, 2025. Submitted Dec 2025.
  4. D. A. Vargas, R. D. Falgout, S. Guenther, and J. B. Schroder, Accelerating Multigrid Reduction in Time with Automated Coarse-Grid Runge-Kutta Theta-Methods. Numerical Linear Algebra with Applications. Submitted Dec 2025.
  5. A. Ali, J. J. Brannick, K. Kahl, O. A. Krzysik, J. B. Schroder, and B. S. Southworth, Generalized Optimal AMG Convergence Theory for Nonsymmetric and Indefinite Problems. SIAM Journal on Scientific Computing, pp. S89-S111. 0 (2025).  PDF
  6. B. Boyce, N. Bianco, K. Fitzgerald, D. Cillessen, N. Brown, J. Carroll, A. Garland, K. Bassett, and J. B. Schroder, Toughness from Imagery: Extracting More from Failure Analysis Using Deep Convolutional Neural Networks. Journal of Failure Analysis and Prevention, Springer. pp 1-21. (2024).  PDF
  7. H. De Sterck, R. D. Falgout, O. A. Krzysik, and J. B. Schroder, Parallel-in-Time Solution of Hyperbolic PDE Systems via Characteristic-Variable Block Preconditioning. SIAM Journal on Scientific Computing, pp. S337-S363. 0 (2025).  PDF
  8. H. De Sterck, R. D. Falgout, O. A. Krzysik, and J. B. Schroder, Parallel-in-Time Solution of Scalar Nonlinear Conservation Laws. SIAM Journal on Scientific Computing, pp. A3134-A3160. 47 (2025).  PDF
  9. E. C. Cyr, J. Hahne, N. S. Moore, J. B. Schroder, B. S. Southworth, and D. A. Vargas, TorchBraid: High-Performance Layer-Parallel Training of Deep Neural Networks with MPI and GPU Acceleration. ACM Transactions on Mathematical Software, pp. 1-30. 51 (2025).  PDF
  10. F. Danieli, B. S. Southworth, and J. B. Schroder, Space-Time Block Preconditioning for Incompressible Resistive Magnetohydrodynamics. Numerical Linear Algebra with Applications, pp 1-14. 32 (2025).  PDF
  11. A. Ali, J. Brannick, K. Kahl, O. A. Krzysik, J. B. Schroder, and B. S. Southworth, Constrained Local Approximate Ideal Restriction for Advection-Diffusion Problems. SIAM Journal on Scientific Computing, pp. S96-S122. 46 (2024).  PDF
  12. H. De Sterck, R. D. Falgout, O. A. Krzysik, and J. B. Schroder, Efficient Multigrid Reduction-in-Time for Method-of-Lines Discretizations of Linear Advection. Journal of Scientific Computing, pp. 1-31. 96 (2023).  PDF
  13. D. A. Vargas, R. D. Falgout, S. Guenther, and J. B. Schroder, Multigrid Reduction in Time for Chaotic Dynamical Systems. SIAM Journal on Scientific Computing, pp. A2019-A204. 45 (2023).  PDF
  14. C. Janna, A. Franceschini, J. B. Schroder, and L. N. Olson, Parallel Energy-Minimization Prolongation for Algebraic Multigrid. SIAM Journal on Scientific Computing, pp A2561-A2584. 45 (2023).  PDF
  15. N. Bell, L. N. Olson, J. B. Schroder, and B. S. Southworth, PyAMG: Algebraic Multigrid Solvers in Python. Journal of Open Source Software. 2023.  PDF
  16. S. M. Guzik, J. Christopher, X. Gao, J. B. Schroder, and R. D. Falgout, On the Use of a Multigrid-Reduction-in-Time Algorithm for Multiscale Convergence of Turbulent Simulations. Computers and Fluids. 2023.  PDF
  17. J. Christopher, X. Gao, R. D. Falgout, J. B. Schroder, and S. M. Guzik, Applying Time-Parallelization to Turbulent Flows. AIAA. 2022.  PDF
  18. M Sugiyama, J. B. Schroder, B. S. Southworth, and S. Friedhoff, Weighted Relaxation for Multigrid Reduction in Time. Numerical Linear Algebra with Applications. Submitted. (2021).  PDF
  19. A. Hessenthaler, R. D. Falgout, J. B. Schroder, D. Nordsletten, and O. Roehrle, Time-Periodic Steady-State Solution of Fluid-Structure Interaction and Cardiac Flow Problems through Multigrid-Reduction-in-Time. Computer Methods in Applied Mechanics and Engineering. Accepted. (2021).  PDF
  20. R. D. Falgout, T. A. Manteuffel, B. O'Neill, and J.B. Schroder, Multigrid Reduction in Time with Richardson Extrapolation. Electronic Transactions on Numerical Analysis, pp. 210-233. 54 (2021).  PDF
  21. E. C. Cyr, S. Guenther, and J. B. Schroder, Multilevel Initialization for Layer-Parallel Deep Neural Network Training. International Journal of Computing and Visualization in Science and Engineering, pp. 1-9. 1 (2021).  PDF
  22. J. Christopher, X. Gao, S. M. Guzik, R. D. Falgout, and J. B. Schroder, A Space-Time Parallel Algorithm with Adaptive Mesh Refinement for Computational Fluid Dynamics. Computing and Visualization in Science, Springer, pp. 1-19. 23 (2020).  PDF
  23. B. W. Ong and J. B. Schroder, Applications of Time Parallelization. Computing and Visualization in Science, Springer, pp. 1-15. 23 (2020).  PDF
  24. A. Hessenthaler, B. S. Southworth, D. Nordsletten, O. Roehrle, R. D. Falgout, and J. B. Schroder, Multilevel Convergence Analysis of Multigrid-Reduction-in-Time. SIAM Journal on Scientific Computing, pp. A771-A796. 42 (2019).   PDF
  25. S. Guenther, L. Ruthotto, J. B. Schroder, E. C. Cyr, and N. R. Gauger, Layer-Parallel Training of Deep Residual Neural Networks. SIAM Journal of Data Science (SIMODS), pp. 1-23. 2 (2020).   PDF
  26. J. Christopher, X. Gao, S. Guzik, R. D. Falgout, and J. B. Schroder, Parallel In Time for a Fully Space-Time Adaptive Mesh Refinement Algorithm. AIAA SciTech Forum, pp. 1-10. (Jan, 2020).  PDF
  27. S. Guenther, R. D. Falgout, P. Top, C. S. Woodward, and J. B. Schroder, Parallel-in-Time Solution of Power Systems with Unscheduled Events. 2019 Power and Energy Society General Meeting (PESGM), IEEE, pp. 1-5. (2019).  PDF
  28. A. Nagel, D. Logashenko, J. B. Schroder, and U. M. Yang, Numerical Methods and Solvers for Large Scale Hydrogeological Flow Problems in Porous Media. Transport in Porous Media, Springer, pp. 363-390. 130 (2019).  PDF
  29. H. De Sterck, R. D. Falgout, A. J. M. Howse, S. P. MacLachlan, and J. B. Schroder, Parallel-in-Time Multigrid with Adaptive Spatial Coarsening for the Linear Advection and Inviscid Burgers Equations. SIAM Journal on Scientific Computing, pp. 538-565. 41 (2019).  PDF
  30. S. Guenther, N. R. Gauger, and J. B. Schroder, A Non-Intrusive Parallel-in-Time Approach for Simultaneous Optimization with Unsteady PDEs. Optimization Methods and Software, pp. 1-16. (2018).  PDF
  31. J. B. Schroder, M. Lecouvez, R. D. Falgout, C. S. Woodward, and P. Top, Parallel-in-Time Solution of Power Systems with Scheduled Events. 2018 Power and Energy Society General Meeting (PESGM), IEEE, pp. 1-5. (2018).  PDF
  32. A. Hessenthaler, D. Nordsletten, O. Roehrle, J. B. Schroder, and R. D. Falgout, Convergence of the Multigrid-Reduction-in-Time Algorithm for the Linear Elasticity Equations. Numerical Linear Algebra with Applications, pp. 1-18. 25 (2018).  PDF
  33. S. Guenther, N. R. Gauger, and J. B. Schroder, A Non-Intrusive Parallel-in-Time Adjoint Solver with the XBraid Library. Computing and Visualization in Science, Springer, pp. 85-95. 19 (2018).  PDF
  34. T. A. Manteuffel, L. N. Olson, J. B. Schroder, and B. S. Southworth, A Root-Node Based Algebraic Multigrid Method. SIAM Journal on Scientific Computing, pp. 723-756. 39 (2017).  PDF
  35. R. D. Falgout, T. A. Manteuffel, B. O'Neill, and J. B. Schroder, Multigrid Reduction in Time for Nonlinear Parabolic Problems: A Case Study. SIAM Journal on Scientific Computing, pp. 298-322. 39 (2017).  PDF
  36. V. Dobrev, Tz. Kolev, N. A. Petersson, and J. B. Schroder, Two-level Convergence Theory for Multigrid Reduction in Time (MGRIT). SIAM Journal on Scientific Computing, pp. 501-527. 39 (2017).  PDF
  37. R. D. Falgout, S. Friedhoff, Tz. V. Kolev, S. P. MacLachlan, J. B. Schroder, and S. Vandewalle, Multigrid Methods with Space-Time Concurrency. Computing and Visualization in Science, Springer, pp. 123-143. 18 (2017).  PDF
  38. A. Bienz, R. D. Falgout, W. Gropp, L. N. Olson, and J. B. Schroder, Reducing Parallel Communication in Algebraic Multigrid Through Sparsification. SIAM Journal on Scientific Computing, pp. 332-357. 38 (2016).  PDF
  39. H. Gahvari, V. A. Dobrev, R. D. Falgout, Tz. V. Kolev, J. B. Schroder, M. Schulz, and U. M. Yang, A Performance Model for Allocating the Parallelism in a Multigrid-in-Time Solver. The 7th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS16), Supercomputing 16.  PDF
  40. C. Ketelsen, T. Manteuffel, and J. B. Schroder, Least-Squares Finite-Element Discretization of the Neutron Transport Equation in Spherical Geometry. SIAM Journal on Scientific Computing, pp. 71-89. 37 (2015).  PDF
  41. R. D. Falgout, S. Friedhoff, Tz. V. Kolev, S. P. MacLachlan, and J. B. Schroder, Parallel Time Integration with Multigrid. SIAM Journal on Scientific Computing, pp. 635-661. 36 (2014).  PDF
  42. R. D. Falgout and J. B. Schroder. Non-Galerkin Coarse Grids for Algebraic Multigrid. SIAM Journal on Scientific Computing, pp. 309-334. 36 (2014).  PDF
  43. J. B. Schroder. Smoothed Aggregation Solvers for Anisotropic Diffusion. Numerical Linear Algebra with Applications, pp. 296-312. 19 (2012).  PDF
  44. L. N. Olson, J. B. Schroder, and R. S. Tuminaro. A General Interpolation Strategy for Algebraic Multigrid Using Energy Minimization. SIAM Journal on Scientific Computing, pp. 966-991. 33 (2011).  PDF
  45. L. N. Olson and J. B. Schroder. Smoothed Aggregation Multigrid Solvers for High-Order Discontinuous Galerkin Methods for Elliptic Problems. Journal of Computational Physics, pp. 6959-6976. 230 (2011).  PDF
  46. L. N. Olson and J. B. Schroder. Smoothed Aggregation for Helmholtz Problems. Numerical Linear Algebra with Applications, pp. 361-386. 17 (2010).  PDF
  47. L. N. Olson, J. B. Schroder, and R. S. Tuminaro. A New Perspective on Strength Measures in Algebraic Multigrid. Numerical Linear Algebra with Applications, pp. 713-733. 17 (2010).  PDF

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Reports
  1. R. D. Falgout and J. B. Schroder, An Approaching Paradigm Shift for Scientific Computing. (2023). LLNL Technical Report, LLNL-TR-851068.  PDF
  2. J. Brannick, S. P. MacLachlan, J. B. Schroder, and B. S. Southworth. The Role of Energy Minimization in Algebraic Multigrid Interpolation. (2019).  PDF
  3. N. Abel, J. Chaudhry, R. D. Falgout, and J. B. Schroder, Multigrid-Reduction-in-Time for the Rotating Shallow Water Equations. (2020). LLNL Technical Report LLNL-TR-813511.  PDF
  4. J. B. Schroder, Parallelizing Over Artificial Neural Network Training Runs with Multigrid. (2017). LLNL Technical Report LLNL-JRNL-736173.  PDF
  5. J. B. Schroder, On the Use of Artificial Dissipation for Hyperbolic Problems and Multigrid Reduction in Time (MGRIT). (2018). LLNL Technical Report LLNL-TR-750825.  PDF
  6. A. J. M. Howse, in collaboration with H. De Sterck, R. D. Falgout, S. P. Machlachlan, and J. B. Schroder, Multigrid Reduction in Time with Adaptive Spatial Coarsening for the Linear Advection Equation, Student paper winner. Eighteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. (2017).
  7. R. D. Falgout, T. A. Manteuffel, J. B. Schroder, and B. Southworth, Parallel-in-Time for Moving Meshes. (2016). LLNL Technical Report LLNL-TR-681918.  PDF
  8. R. D. Falgout, A. Katz, Tz. V. Kolev, J. B. Schroder, A. Wissink, and U. M. Yang, Parallel Time Integration with Multigrid Reduction for a Compressible Fluid Dynamics Application. (2014). LLNL Technical Report LLNL-JRNL-663416.  PDF
  9. S. Friedhoff, R. Falgout, T. Kolev, S. MacLachlan, and J. Schroder. A Multigrid-In-Time Algorithm for Solving Evolution Equations in Parallel. Student paper winner. Sixteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March, 2013.
  10. L. N. Olson and J. B. Schroder. Components of a More Robust Multilevel Solver for Emerging Architectures and Complex Applications. In SciDAC 2011 (2011).  PDF
  11. J. B. Schroder. Generalizing Smoothed Aggregation-Based Algebraic Multigrid. Ph.D. thesis. University of Illinois at Urbana-Champaign, Department of Computer Science. (2010).  PDF
  12. J. B. Schroder, R. S. Tuminaro, and L. N. Olson, Generalized Strength-of-Connection in Algebraic Multigrid. CSRI Summer Proceedings 2007. pp. 12-26. (2007).
  13. V. E. Howle, J. B. Schroder, and R. S. Tuminaro. The Effect of Boundary Conditions within Pressure-Convection Diffusion Preconditioners. Sandia National Labs Technical Report #2006-4466. July 2006.

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Presentations
  1. Structure Preserving AMG Strategies for PDE Systems, with a Focus on Stokes Equations, 41st Colorado Conference On Iterative and Multigrid Methods, Boulder, CO, June 2026.
  2. Algebraic Multigrid via Energy-Minimization for Symmetric and Non-Symmetric Problems, Department of Mathematics, University of Wuppertal, Germany, June 2026. Invited colloquium.
  3. Scalable Parallel-in-Time with Multigrid: Theory, Applications, and Recent Developments, University of Toulouse, France, July 2025. Invited talk.
  4. Structure Preserving AMG Coarsening and Interpolation for PDE Systems, DD29: 29th International Conference on Domain Decomposition Methods, Milan, Itay, June 2025.
  5. Multigrid Reduction in Time: Theory and Applications, University of Cologne, Department of Mathematics and Computer Science, May 2025. Invited talk.
  6. Scalable Parallel-in-Time with Multigrid: Theory, Applications, and Recent Developments, Go20 Conference on Scientific Computing and Software, Gozo, Malta, May 2025. Invited talk.
  7. Scalable and Non-Intrusive Parallel-in-Time with Multigrid Reduction, Juelich Supercomputing Center, Juelich, Germany, February 2025. Invited talk.
  8. High-Performance Layer-Parallel Training of DNNs with MPI and GPU Acceleration, Institute of Mathematics, Hamburg University of Technology, Germany, January 2025. Invited talk.
  9. TorchBraid: High-Performance Layer-Parallel Training of Deep Neural Networks with MPI and GPU Acceleration, Department of Mathematics, University of Wuppertal, Germany, November 2024. Invited colloquium.
  10. Generalized Optimal Algebraic Multigrid (AMG) Convergence Theory for Nonsymmetric and Indefinite Problems, GAMM Workshop on Applied and Numerical Linear Algebra 2024, University of Goettingen, Germany, September 2024.
  11. Scalable Multigrid for Deep Learning Using MPI+GPU, 2024 Conference on Preconditioning, Georgia Institute of Technology, Atlanta, Georgia, June 2024. Invited plenary.
  12. A Parallel-in-Time Algorithm for Chaotic Systems, 12th Parallel-in-Time Workshop, Hamburg, Germany, July 2023.
  13. Generalizing Approximate Ideal Restriction (AIR) Algebraic Multigrid, Twenty-First Copper Mountain Conference on Multigrid, Copper Mountain, CO, April 2023.
  14. Time-Parallel Methods for Traditionally Challenging Problems, SIAM Conference on Computational Science and Engineering (CSE23), Amsterdam, Netherlands. Feb. 26-March 3, 2023. Minisymposium organizer.
  15. Layer-Parallel Multi-Level Optimization for Deep Residual Neural Networks, SIAM Conference on Mathematics of Data Science, San Diego, CA, September 2022.
  16. XBraid Tutorial, CBMS Conference -- Parallel Time Integration, Michigan Tech, Michigan. August 2022.
  17. Multigrid-Reduction for Scalable Parallel-in-Time: Theory and Applications with a Focus on Optimization and Machine Learning, Department of Mathematics, University of Wuppertal, Germany, June 2022. Invited colloquium.
  18. Multigrid-Reduction for Scalable Parallel-in-Time: Theory and Applications, Department of Civil, Environmental and Architectural Engineering, University of Padua, Italy, June 2022. Invited colloquium.
  19. Scalable and Non-Intrusive Parallel-in-Time with Multigrid, Department of Mathematics, University of Arizona, April 28th, 2022. Invited Seminar.
  20. Parallel-in-Time with Multigrid: Method, Theory, and Applications, Department of Applied Mathematics, University of Waterloo, December 14th, 2021. Invited Talk.
  21. Multigrid Reduction in Time: Two-Level Convergence Theory with Spatial Coarsening, 10th Parallel-in-time Workshop, Virtual Zoom due to Covid-19, August 2, 2021.
  22. Layer-Parallel Training, Multilevel Network Initialization, and Local Learning, Twenty-first Copper Mountain Conference on Multigrid Methods, Virtual Zoom due to Covid-19, March 29, 2021.
  23. Multigrid-Based Distributed Computing Models for Deep Learning, SIAM Conference on Computational Science and Engineering (CSE21), Virtual Zoom due to Covid-19, March 1, 2021. Minisymposium organizer.
  24. Early Career Panel, SIAM Conference on Computational Science and Engineering (CSE21), Virtual Zoom due to Covid-19. March 2, 2021. Invited speaker.
  25. A General and Scalable Multigrid-Reduction Approach to Parallel-in-Time, Department of Mathematical Sciences, Michigan Tech, Houghton, Michigan. January 22, 2021. Invited colloquium.
  26. The Lake City Algebraic Multigrid Summit, University of Colorado at Boulder, LLNL, UNM. 10/2010, 9/2011, 10/2012, 9/2013, 10/2014, 9/2015, 10/2016, 9/2017, 10/2019, 10/2020.
  27. Parallel-in-Time Training for Deep Residual Neural Networks, 9th Parallel-in-time Workshop, Virtual Zoom due to Covid-19, June 12, 2020.
  28. Layer-Parallel Training and Multilevel Initialization for Deep Residual Neural Networks, 16th Copper Mountain Conference On Iterative Methods, Copper Mountain, Colorado. March 21-26, 2020.
    Abstract accepted, conference canceled due to Covid-19.
  29. Parallel-in-Time with Multigrid: Theory and Applications, Colloquium, Department of Mathematics and Statistics, University of New Mexico. October 24, 2019.
  30. Parallel Multigrid Solvers in Space and Time for Future Architectures, Los Alamos National Laboratory, Math and Physics Division, June 18, 2019. Invited Talk.
  31. Scalable Parallel-in-Time with Multigrid, Bergische University of Wuppertal, Applied Mathematics Group, May 28, 2019. Invited Talk.
  32. Parallel-in-Time and Deep Residual Neural Networks: Layer-Parallelism, Eighth Workshop on Parallel-in-Time Methods: Advanced Parallel-in-Time Algorithms for Computer Simulations in Physical Sciences, Social Sciences and Engineering, Bielefeld, Germany, May 21, 2019.
  33. Layer-Parallel Training of Deep Residual Neural Networks, Nineteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 2019.
  34. Parallel Time Integration, Nineteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 2019. Minisymposium co-organizer.
  35. Parallel-in-Time: A Scalable and Non-Intrusive Approach with Multigrid, Applied Math Seminar, Department of Mathematics and Statistics, University of New Mexico. October 22, 2019.
  36. Parallel Multigrid Solvers for Future Architectures, Sandia National Laboratories, CSRI, Oct. 17, 2018. Invited Talk.
  37. Parallel-in-Time Methods for Highly Concurrent Architectures. DD25, St. Johns, Canada, July 2018. Minisymposium organizer.
  38. Parallel-in-Time Optimization with the General-Purpose XBraid Package. Seventh Workshop on Parallel-in-Time Methods, Roscoff, France, May 3, 2018.
  39. MGRIT for Non-PDE-Based Evolution Processes: Powergrid simulations and neural network training. Fifteenth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. March 2018.
  40. Parallel-in-Time: A Scalable and Non-Intrusive Approach with Multigrid Reduction in Time (MGRIT). Department of Mechanical Engineering, Colorado State University, Fort Collins, Colorado. November 14, 2017. Invited colloquium.
  41. Multigrid Reduction in Time for Non-PDE-Based Evolution Processes: Powergrid Simulations and Neural Network Training. Sixth Workshop on Parallel-in-Time Integration, Centro Congressi Stefano Franscini, Ascona, Switzerland. October 2017.
  42. XBraid Tutorial. Sixth Workshop on Parallel-in-Time Integration, Centro Congressi Stefano Franscini, Ascona, Switzerland. October 2017.
  43. XBraid Tutorial. Eighteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 2017.
  44. Parallel Time Integration. Eighteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 2017. Minisymposium co-organizer.
  45. Space-Time Multigrid Methods Minisymposium. SIAM Conference on Computational Science and Engineering (CSE), Atlanta, Georgia. March 2017. Minisymposium co-organizer.
  46. Space-Time Adaptive Meshing with the XBraid Library. Twenty-Fourth International Conference on Domain Decomposition Methods, Svalbard, Norway. February 2017.
  47. Two-level Convergence Theory for Multigrid Reduction in Time (MGRIT). Fifth Workshop on Parallel-in-Time Integration, Banff International Research Station, Canada. November 2016.
  48. Multigrid Reduction in Time: Recent Theoretical Results. Fourteenth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. March 22, 2016.
  49. Multigrid Reduction in Time (MGRIT): A Flexible and Scalable Approach to Parallel-in-Time. Monash Workshop on Numerical PDEs, Melbourne, Australia. February 17, 2016. Invited plenary.
  50. Multigrid Reduction in Time (MGRIT): An Overview. Fourth Workshop on Parallel-in-Time Integration, Dresden, Germany. May 27, 2015.
  51. A General Purpose Parallel-in-Time Approach. SIAM Conference on Computational Science and Engineering (CSE), Salt Lake City, Utah. March 18, 2015. Minisymposium organizer.
  52. Multigrid Reduction in Time: A Flexible and Non-Intrusive Method. Third Workshop on Parallel-in-Time Integration, Julich, Germany. May 27, 2014.
  53. Theoretical Advances Regarding Non-Galerkin Coarse-Grid Operators for Algebraic Multigrid. Thirteenth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. April 9, 2014.
  54. Non-Galerkin Coarse-Grid Operators for Parallel Algebraic Multigrid. Sixteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 19, 2013.
  55. Energy-Minimization Interpolation for Adaptive Algebraic Multigrid. SIAM Conference on Applied Linear Algebra, Valencia, Spain. June 18-22, 2012.
  56. Non-Galerkin Coarse-Grid Operators for Parallel Algebraic Multigrid. Twelfth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. March 27, 2012.
  57. PyAMG Tutorial. Twelfth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. March 28, 2012.
  58. A General Energy-Minimization Strategy for Interpolation in Algebraic Multigrid. Seventh International Congress on Industrial and Applied Mathematics, Vancouver, Canada. July 21, 2011.
  59. PyAMG Tutorial. Fifteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 31, 2011.
  60. Smoothed Aggregation Solvers for Anisotropic Diffusion. Fifteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 28, 2011.
  61. Generalizing Smoothed Aggregation-Based Algebraic Multigrid. Tech-X Corporation, Boulder, Colorado. July 29, 2010.
  62. A General Interpolation Strategy for Algebraic Multigrid Using Energy Minimization. Eleventh Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. April 5, 2010.
  63. Smoothed Aggregation Multigrid for Helmholtz Problems. Fourteenth Copper Mountain Conference on Multigrid Methods, Copper Mountain, Colorado. March 23, 2009.
  64. A General Strength-of-Connection Concept in AMG. Tenth Copper Mountain Conference on Iterative Methods, Copper Mountain, Colorado. April 7, 2008.
  65. Stability and Load Balancing in a NASA Global Circulation Model. Southeast ACM Conference, Gatlinburg, Tennessee. November 22, 2003.

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