World's Best Scientists 2026 revealed!

Overview

Houman Owhadi is affiliated with the California Institute of Technology in the United States. Their research spans primarily in the field of Computer Science, with significant contributions to subfields such as Artificial Intelligence, Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty, Computational Mechanics, and Control and Systems Engineering.

The scientist's work focuses on topics including Gaussian Processes and Bayesian Inference, Model Reduction and Neural Networks, Probabilistic and Robust Engineering Design, Neural Networks and Applications, Machine Learning and Data Classification, Statistical Methods and Inference, and Numerical Methods in Inverse Problems.

Recent papers authored or co-authored by Owhadi include:

  • Solving and learning nonlinear PDEs with Gaussian processes, 2021, Journal of Computational Physics
  • Learning dynamical systems from data: A simple cross-validation perspective, part I: Parametric kernel flows, 2021, Physica D Nonlinear Phenomena
  • Consistency of empirical Bayes and kernel flow for hierarchical parameter estimation, 2021, Mathematics of Computation
  • Simple, low-cost and accurate data-driven geophysical forecasting with learned kernels, 2021, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • One-shot learning of stochastic differential equations with data adapted kernels, 2022, Physica D Nonlinear Phenomena

Frequent co-authors include:

  • Boumediene Hamzi
  • Bamdad Hosseini
  • Pau Batlle
  • Andrew M. Stuart
  • Clint Scovel

Owhadi's research has been published in venues such as:

  • arXiv (Cornell University)
  • Physica D Nonlinear Phenomena
  • SSRN Electronic Journal
  • Journal of Computational Physics
  • Mathematics of Computation

They have also contributed to book publications, including a publication with Springer International Publishing titled Kernel Mode Decomposition and the Programming of Kernels (2021).

Best Publications

  • Handbook of Uncertainty Quantification

    Roger Ghanem;David Higdon;Houman Owhadi

  • A non-adapted sparse approximation of PDEs with stochastic inputs

    Alireza Doostan;Houman Owhadi

  • Metric‐based upscaling

    Houman Owhadi;Lei Zhang

  • Bayesian Numerical Homogenization

    Houman Owhadi

  • Multigrid with Rough Coefficients and Multiresolution Operator Decomposition from Hierarchical Information Games

    Houman Owhadi

  • Numerical coarsening of inhomogeneous elastic materials

    Lily Kharevych;Patrick Mullen;Houman Owhadi;Mathieu Desbrun

  • Optimal Uncertainty Quantification

    Houman Owhadi;Clint Scovel;Timothy John Sullivan;Mike McKerns

  • Stochastic Variational Integrators

    Nawaf Bou-Rabee;Houman Owhadi

  • Long-Run Accuracy of Variational Integrators in the Stochastic Context

    Nawaf Bou-Rabee;Houman Owhadi

  • Polyharmonic homogenization, rough polyharmonic splines and sparse super-localization

    Houman Owhadi;Lei Zhang;Leonid Berlyand

  • Nonintrusive and Structure Preserving Multiscale Integration of Stiff ODEs, SDEs, and Hamiltonian Systems with Hidden Slow Dynamics via Flow Averaging

    Molei Tao;Houman Owhadi;Jerrold E. Marsden

  • Solving and learning nonlinear PDEs with Gaussian processes

    Yifan Chen;Bamdad Hosseini;Houman Owhadi;Andrew M. Stuart

  • Numerical homogenization of the acoustic wave equations with a continuum of scales

    Houman Owhadi;Lei Zhang

  • On the equilibrium of simplicial masonry structures

    Fernando de Goes;Pierre Alliez;Houman Owhadi;Mathieu Desbrun

  • Localized Bases for Finite-Dimensional Homogenization Approximations with Nonseparated Scales and High Contrast

    Houman Owhadi;Lei Zhang

  • Flux Norm Approach to Finite Dimensional Homogenization Approximations with Non-Separated Scales and High Contrast

    Leonid Berlyand;Houman Owhadi

  • Kernel Flows: From learning kernels from data into the abyss

    Houman Owhadi;Gene Ryan Yoo

  • Rigorous verification, validation, uncertainty quantification and certification through concentration-of-measure inequalities

    L.J. Lucas;H. Owhadi;M. Ortiz

  • Non-intrusive and structure preserving multiscale integration of stiff ODEs, SDEs and Hamiltonian systems with hidden slow dynamics via flow averaging

    Molei Tao;Houman Owhadi;Jerrold E. Marsden

  • Localized bases for finite dimensional homogenization approximations with non-separated scales and high-contrast

    Houman Owhadi;Lei Zhang

Frequent Co-Authors

Timothy Sullivan
Timothy Sullivan University of Canterbury
Jerrold E. Marsden
Jerrold E. Marsden California Institute of Technology
Clarence W. de Silva
Clarence W. de Silva University of British Columbia
Mathieu Desbrun
Mathieu Desbrun California Institute of Technology
Ufuk Topcu
Ufuk Topcu The University of Texas at Austin
Andrew M. Stuart
Andrew M. Stuart California Institute of Technology
Gérard Ben Arous
Gérard Ben Arous Courant Institute of Mathematical Sciences
Richard M. Murray
Richard M. Murray California Institute of Technology
Roger Ghanem
Roger Ghanem University of Southern California
Jun Yao
Jun Yao China University of Petroleum, Beijing

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