Presentations 
 Ju, L., J. Zhang, and Q. Du, 2015: Fast and accurate algorithms for simulating coarsening dynamics of CahnHilliard equations, Computational Materials Science, Vol. 108, pp. 272282, 2015.
 Zhu L., L. Ju, and W.D. Zhao, 2016: Fast highorder compact exponential time differencing RungeKutta methods for secondorder semilinear parabolic equations, Journal of Scientific Computing, Vol. 67, pp. 10431065, 2016.
 H. Zhu, N. Petra, G. Stadler, T. Isaac, T. J. R. Hughes, O. Ghattas: Inversion of geothermal heat flux in a thermomechanically coupled nonlinear Stokes ice sheet model. The Cryosphere, 10, 14771494, (2016). http://dx.doi.org/10.5194/tc1014772016
 H. Sundar, G. Stadler and G. Biros: Comparison of multigrid algorithms for highorder continuous finite element discretizations, Numerical Linear Algebra with Applications, 22(4), pp. 664680, (2015). http://dx.doi.org/10.1002/nla.1979
 Isaac, T., G. Stadler and O. Ghattas. 2015. Solution of nonlinear Stokes equations discretized by highorder finite elements on nonconforming and anisotropic meshes, with application to ice sheet dynamics, SIAM Journal of Scientific Computing, 37(6), pp. B804B833, (2015).
 Zou, X., K. Wu, D. A. Boyuka, D. F. Martin, S. Byna, Houjun, K. Bansal, T. J. Ligocki, H. Johansen, and N. F. Samatova, 2015: "Parallel In Situ Detection of Connected Components Adaptive Mesh Refinement Data", Proceedings of the Cluster, Cloud and Grid Computing (CCGrid) 2015, 2015.
 Goldberg, D., P. Heimbach, I. Joughin, and B. Smith, 2015. Committed retreat of Smith, Pope, and Kohler Glaciers over the next 30 years inferred by transient model calibration. The Cryosphere, 9, 2429–2446, doi:10.5194/tc924292015.
 Kalmikov, A. and P. Heimbach. 2014. A Hessianbased method for Uncertainty Quantification in Global Ocean State Estimation. SIAM J. Scientific Computing (Special Section on Planet Earth and Big Data), 36(5), S267–S295, doi:10.1137/130925311.
 Zhang, T., L. Ju, W. Leng, S. Price, and M. Gunzburger, 2015: Thermomechancially coupled modelling for landterminating glaciers: a comparison of twoDimensional, firstorder and threedimensional, fullStokes approaches, J. Glaciol., 61(227), doi: 10.3189/2015JoG14J220
 Cornford, S, D. F. Martin, A. J. Payne, E. G. Ng, A. M. Le Brocq, R. M. Gladstone, T. L. Edwards,
S. R. Shannon, C. Agosta, M. R. van den Broeke, H. H. Hellmer, G. Krinner, S. R. M. Ligtenberg,
R. Timmermann, and D. G. Vaughan, 2015. Centuryscale simulations of the response of the West Antarctic Ice Sheet to a warming climate, The Cryosphere, 9, 15791600
 Tezaur, I. K., M. perego, A. G. Salinger, R. S. Tuminaro, and S. F. Price, 2015: On the Scalability of the Albany/FELIX firstorder Stokes Approximation ice Sheet Solver for LargeScale Simulations of the Greenland and Antarctic ice Sheets. Procedia Comp. Sci., 51, pp. 20262035.
 Isaac, T., N. Petra, G. Stadler and O. Ghattas. 2014. Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for largescale problems, with application to flow of the Antarctic ice sheet, Journal of Computational Physics, online first, doi:10.1016/j.jcp.2015.04.047
 Tezaur, I., M. Perego, A. Salinger, R. Tuminaro, and S. Price. 2015. Albany/FELIX: a parallel, scalable and robust, finite element, firstorder Stokes approximation ice sheet solver built for advanced analysis, Geophys. Model Devel., 8, doi:10.5194/gmd811972015.
 Leng, W., L. Ju, Y. Xie, T. Cui, and M. Gunzburger. 2014. Finite element threedimensional Stokes ice sheet dynamics model with enhanced local mass conservation, J. Comput. Phys., 274, pp. 299311.
 Leng, W., L. Ju, M. Gunzburger, and S. Price. 2014. A parallel computational model for threedimensional, thermomechanical Stokes flow simulations of glaciers and ice sheets, Commun. Comp. Phys., DOI:10.4208/cicp.310813.010414a.
 Ju, L., X. Liu, and W. Leng. 2014. Compact implicit integration factor methods for a family of semilinear fourthorder parabolic equations, Discrete and Continuous Dynamical Systems Series B, 19, pp. 16671687.
 Perego, M., S.F. Price, and G. Stadler. 2014. Optimal ice sheet model initial conditions for coupling to climate models. J. Geophys. Earth Surf., DOI:10.1002/2014JF003181.
 Petra, N., J. Martin, G. Stadler and O. Ghattas. 2014. A computational framework for infinitedimensional Bayesian inverse problems: Part II. Stochastic Newton MCMC with application to ice sheet flow inverse problems; SIAM Journal of Scientific Computing 36(4), A15251555.
 Chen, Q., M. Gunzburger, and M. Perego. 2013. Wellposedness results for a nonlinear Stokes problem arising in glaciology, SIAM J. Math. Anal., 45(5), 27102733.
 Ju, L., J. Zhang, L. Zhu and Q. Du. 2014. Fast explicit integration factor methods for semilinear parabolic equations, Journal of Scientific Computing, DOI:10.1007/s1091501498629.
 Goldberg, D.N. and P. Heimbach. 2013. Parameter and state estimation with a timedependent adjoint marine ice sheet model. The Cryosphere, 7, 16591678.
 Straneo, F. and P. Heimbach. 2013. North Atlantic warming and the retreat of Greenland's outlet glaciers. Nature, 36(504), doi:10.1038/nature12854.
 Chen, Q., M. Gunzburger, and M. Perego. 2013. Wellposedness results for a nonlinear Stokes problem arising in glaciology, SIAM J. Math. Anal., 45(5), 27102733.
 Pattyn, F. et al (inc. D. Martin). 2013. Groundingline migration in planview marine icesheet models: results of the ice2sea MISMIP3d intercomparison, Journal of Glaciology, 59(215), 410422, doi: 10.3189/2013JoG12J129.
 Wei Leng, Lili Ju, Max Gunzburger, and S. Price: Manufactured solutions and the verification of threedimensional Stokes icesheet models.
 Scalable solvers for highly heterogeneous nonlinear Stokes flow discretized with adaptive highorder finite elements (no slides available)
 Computational methods for Bayesian inverse problems governed by PDEs, with application to studying the dynamics of ice sheets (no slides available)
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 Boghozian, A.B. "A pythonbased land ice verification and validation toolkit to evaluate ice sheet models," AMS Annual Meeting, Atlanta, GA, USA, Jan., 2014
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