• Title
    Computational Scientist
  • Email
    hill134@llnl.gov
  • Phone
    (925) 422-5201
  • Organization
    Not Available

Dr. Judith Hill joined Livermore Computing as a Computational Scientist in 2021. She specializes in the development, implementation, and application of numerical methods for massively parallel computers to a variety of applications including computational fluid dynamics, climate science, and chemistry.  Her interests include multiphysics and multidomain coupling methods, implicit interface methods, and large-scale PDE-constrained optimization. 

Prior to joining Livermore Computing, Judy was the Group Leader for the Scientific Computing Group at the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, and she also served as Program Manager for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program at the Leadership Computing Facilities at ORNL and ANL.  While at ORNL, Judy established and led the ECP Application Integration effort aimed at leveraging existing application readiness efforts at the three ASCR computing facilities (OLCF, ALCF and NERSC) for the ECP application projects.  She has extensive experience in readying scientific applications for new massively parallel architectures such as Summit and the forthcoming Frontier.

Deeply committed to professional service, Judy is currently the Program Director for the SIAM Computational Science and Engineering Activity Group and was previously the Secretary from 2019-2020.  She serves as a reviewer for Computer Physics Communications, the International Journal of Numerical Methods in Engineering, Applied Numerical Mathematics, Supercomputing, INCITE, and both DOD and DOE ASCR proposals and has served on the programming committee for several conferences. In 2005, she was named the Fred Howes Scholar in Computational Science for her leadership, character and technical achievement in the field of computational science. 

Judy earned her Ph.D. in Computational Science and Engineering from Carnegie Mellon University.

W. Lei, Y. Ruan, E. Bozdag, D. Peter, M. Lefebvre, D. Komatitsch, J. Tromp, J. Hill, N. Podhorszki, and D. Pugmire. Global Adjoint Tomography – Model GLAD-M25.  Geophysics Journal International.  To appear.

Y. Ruan, W. Lei, M. Lefebvre, R. Modrak, J. Smith, R. Orsvuran, E. Bozdag, J. Hill, N. Podhorszki, D. Pugmire, and J. Tromp.  A new Generation Earth Mantle Model from Global Adjoint Tomography.  Acta Geologica Sinica.  93 (S1).  2019.

M. Lefebvre, Y. Chen, W. Lei, D. Luet, Y. Ruan, E. Bozdag, J. Hill, D. Komatitsch, L. Krischer, D. Peter, N. Podhorszki, J. Smith, and J. Tromp. "Data and Workflow Management for Exascale Global Adjoint Tomography", in Exascale Scientific Applications: Scalability and Performance Portability. T. Straatsma, K. Antypas, and T. Williams, eds. CRC Press. 2017.

D. Pugmire, E. Bozdag, M. Lefebvre, J. Tromp, D. Komatitsch, D. Peter, N. Podhorszki, and J. Hill.  Pillars of the Mantle: Imaging the Interior of the Earth with Adjoint Tomography.  PEARC17: Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact.  75.  2017.

E. Bozdag, D. Peter, M. Lefebvre, D. Komatitsch, J. Tromp, J. Hill, N. Podhorszki, and D. Pugmire. Global Adjoint Tomography: First-Generation Model.  Geophysics Journal International.  207 (3).  December, 2016

B. Messer, E. D’Azevedo, J. Hill, W. Joubert, M. Berrill, C. Zimmer.  MiniApps Derived from Production HPC Applications Using Multiple Programming Models.  International Journal of High Performance Computing Applications.  2016.

R.J. Harrison, et. al.  MADNESS: A multiresolution, adaptive numerical environment for scientific simulation. SIAM Journal on Scientific Computing.  38 (5).  2016.

B. Messer, E. D’Azevedo, J. Hill, W. Joubert, S. Laosooksathit, and A. Tharrington.  Developing MiniApps on Modern Platforms Using Multiple Programming Models.  Proceedings of the 2015 IEEE International Conference on Cluster Computing.  October, 2015.

C. Garrett, C. Hauck, and J. Hill.  Optimization and Large Scale Computation of an Entropy Based Moment Closure. Journal of Computational Physics.  December, 2015.

A. Wingen, M.W. Shafer, E.A. Unterberg, J.C. Hill, and D.L. Hillis.  Regularization of soft-X-ray imaging in the DIII-D tokamak.  Journal of Computational Physics.  289.  2015.

N. Boffi, J.C. Hill and M.G. Reuter.  Characterizing the Inverses of Block Tridiagonal, Block Toeplitz Matrices. Computational Science and Discovery.  8.  2015.