Houman Owhadi

Last updated
Houman Owhadi
Alma mater École Polytechnique
EPFL
Known forStatistical numerical approximation
Kernel methods
Uncertainty quantification
AwardsGermund Dahlquist Prize (2019)
Fellow, SIAM (2022)
Scientific career
Fields Applied mathematics
Institutions California Institute of Technology
CNRS
Doctoral advisor Gérard Ben Arous

Houman Owhadi is a professor of Applied and Computational Mathematics and Control and Dynamical Systems in the Computing and Mathematical Sciences department at the California Institute of Technology. [1] He is known for his work in statistical numerical approximation, kernel learning, and uncertainty quantification. [2]

Contents

Academic biography

Owhadi studied at the École polytechnique where he received a M.S. in Mathematics and Physics in 1994 and was a civil servant in the Corps des ponts in 1997. He received his Ph.D. in mathematics from the École Polytechnique Fédérale de Lausanne in 2001, studying under Gérard Ben Arous. He was a CNRS Research Fellow between 2001 and 2004. He joined the California Institute of Technology in 2004 and became Professor of Applied & Computational Mathematics and Control & Dynamical Systems in 2011. [3]

Research

Owhadi is noted for his work in the field of statistical numerical approximation, which explores the interplay between numerical approximation and statistical inference, [4] [5] . His work has influenced the field of probabilistic numerics [6] which combines approaches from machine learning and applied mathematics.

He has done extensive work in uncertainty quantification and has been editor of the Handbook of Uncertainty Quantification [7] and the SIAM/ASA Journal on Uncertainty Quantification. [8]

He has also worked on Gaussian processes and kernel methods, the problem of kernel learning, and numerical homogenization.[ citation needed ]

Awards and honors

Owhadi won the EPFL doctorate award for his thesis in 2001. [9] He was an invited lecturer at the SIAM conference on Computational Science and Engineering in 2015 [10] and a plenary speaker at the XVI International Conference on Hyperbolic Problems. [11] In 2019, he received the SIAM Germund Dahlquist Prize. [12] He was elected a SIAM fellow in 2022 for "outstanding contributions in statistical numerical approximation, kernel learning, and uncertainty quantification". [13]

Related Research Articles

Computational science, also known as scientific computing, technical computing or scientific computation (SC), is a division of science that uses advanced computing capabilities to understand and solve complex physical problems. This includes

Society for Industrial and Applied Mathematics (SIAM) is a professional society dedicated to applied mathematics, computational science, and data science through research, publications, and community. SIAM is the world's largest scientific society devoted to applied mathematics, and roughly two-thirds of its membership resides within the United States. Founded in 1951, the organization began holding annual national meetings in 1954, and now hosts conferences, publishes books and scholarly journals, and engages in advocacy in issues of interest to its membership. Members include engineers, scientists, and mathematicians, both those employed in academia and those working in industry. The society supports educational institutions promoting applied mathematics.

Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known. An example would be to predict the acceleration of a human body in a head-on crash with another car: even if the speed was exactly known, small differences in the manufacturing of individual cars, how tightly every bolt has been tightened, etc., will lead to different results that can only be predicted in a statistical sense.

<span class="mw-page-title-main">Alexandre Chorin</span> American mathematician

Alexandre Joel Chorin is an American mathematician known for his contributions to computational fluid mechanics, turbulence, and computational statistical mechanics.

<span class="mw-page-title-main">Germund Dahlquist</span> Swedish mathematician

Germund Dahlquist was a Swedish mathematician known primarily for his early contributions to the theory of numerical analysis as applied to differential equations.

<span class="mw-page-title-main">Andrew M. Stuart</span> British mathematician

Andrew M. Stuart is a British and American mathematician, working in applied and computational mathematics. In particular, his research has focused on the numerical analysis of dynamical systems, applications of stochastic differential equations and stochastic partial differential equations, the Bayesian approach to inverse problems, data assimilation, and machine learning.

Desmond John Higham is an applied mathematician and Professor of Numerical Analysis the School of Mathematics at the University of Edinburgh, United Kingdom.

Jesús María Sanz-Serna is a mathematician who specializes in applied mathematics. Sanz-Serna pioneered the field of geometric integration and wrote the first book on this subject. From 1998 to 2006, he was rector of the University of Valladolid.

<span class="mw-page-title-main">Joel Tropp</span>

Joel Aaron Tropp is the Steele Family Professor of Applied and Computational Mathematics in the Computing and Mathematical Sciences Department at the California Institute of Technology. He is known for work on sparse approximation, numerical linear algebra, and random matrix theory.

<span class="mw-page-title-main">Leonid Berlyand</span>

Leonid Berlyand is a Soviet and American mathematician, a professor of Penn State University. He is known for his works on homogenization, Ginzburg–Landau theory, mathematical modeling of active matter and mathematical foundations of deep learning.

Tang Tao is a Chinese mathematician currently serving as President of BNU-HKBU United International College. Tang is a member of the Chinese Academy of Sciences., Fellow of the European Academy of Sciences., Fellow of The World Academy of Sciences for the advancement of science in developing countries (TWAS). He is also a fellow of the Society for Industrial and Applied Mathematics and American Mathematical Society.

<span class="mw-page-title-main">Robert McLachlan (mathematician)</span> New Zealand mathematician

Robert Iain McLachlan is a New Zealand mathematician and Distinguished Professor in the School of Fundamental Sciences, Massey University, New Zealand. His research in geometric integration encompasses both pure and applied mathematics, modelling the structure of systems such as liquids, climate cycles, and quantum mechanics. He is also writes for the public on the subject of climate change policy.

<span class="mw-page-title-main">Jan S. Hesthaven</span> Danish mathematician

Jan S. Hesthaven is a Danish mathematician, currently Vice President for Academic Affairs at EPFL. He is Professor of Mathematics, holds the Chair of Computational Mathematics and Simulation Science (MCSS), and was appointed Vice President for Academic Affairs at EPFL. He is particularly known for contributions to the development, analysis and application of high-order accurate computational methods for time-dependent partial differential equations. He has also contributed substantially to the development of reduced order models and the application of neural networks and machine learning techniques to problems in science and engineering.

This is a comparison of statistical analysis software that allows doing inference with Gaussian processes often using approximations.

The Peter Henrici Prize is a prize awarded jointly by ETH Zurich and the Society for Industrial and Applied Mathematics (SIAM) for "original contributions to applied analysis and numerical analysis and/or for exposition appropriate for applied mathematics and scientific computing". The prize is named in honor of the Swiss numerical analyst Peter Henrici, who was a professor at ETH Zurich for 25 years.

Christian Soize is a French engineer and applied mathematician known for his contributions in computational mechanics and uncertainty quantification. He is Full Professor at the Laboratoire Modélisation et Simulation Multi Echelle at Gustave Eiffel University.

Assyr Abdulle was a Swiss mathematician. He specialized in numerical mathematics.

Probabilistic numerics is an active field of study at the intersection of applied mathematics, statistics, and machine learning centering on the concept of uncertainty in computation. In probabilistic numerics, tasks in numerical analysis such as finding numerical solutions for integration, linear algebra, optimization and simulation and differential equations are seen as problems of statistical, probabilistic, or Bayesian inference.

Bayesian quadrature is a method for approximating intractable integration problems. It falls within the class of probabilistic numerical methods. Bayesian quadrature views numerical integration as a Bayesian inference task, where function evaluations are used to estimate the integral of that function. For this reason, it is sometimes also referred to as "Bayesian probabilistic numerical integration" or "Bayesian numerical integration". The name "Bayesian cubature" is also sometimes used when the integrand is multi-dimensional. A potential advantage of this approach is that it provides probabilistic uncertainty quantification for the value of the integral.

Daniel Kressner is a German numerical analyst. He has a Chair of Numerical Algorithms and High Performance Computing in the Institute of Mathematics at EPF Lausanne.

References

  1. ↑ "Houman Owhadi | Computing + Mathematical Sciences". www.cms.caltech.edu.
  2. ↑ "Professor Owhadi Elected SIAM Fellow". Computing and Mathematical Department of Caltech. 31 March 2022. Retrieved 11 September 2023.
  3. ↑ Owhadi, Houman. "Bio". Research website of Houman Owhadi. Retrieved 11 September 2023.
  4. ↑ Owhadi, Owhadi; Scovel, Clint (2019). Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization. Cambridge University Press. doi:10.1017/9781108594967. ISBN   9781108594967. S2CID   208123760 . Retrieved 11 September 2023.
  5. ↑ Owhadi, Houman; Scovel, Clint; Schäfer, Florian (1 November 2019). "Statistical Numerical Approximation" (PDF). Notices of the American Mathematical Society. 66 (10): 1. doi:10.1090/noti1963. S2CID   204830421.
  6. ↑ Hennig, Philipp; Osborne, Michael A.; Kersting, Hans P. (2022). Probabilistic Numerics: Computation as Machine Learning. Cambridge University Press. p. 8. ISBN   978-1-107-16344-7.
  7. ↑ Ghanem, Roger; Higdon, David; Owhadi, Houman, eds. (2017). Handbook of Uncertainty Quantification. Cham, Switzerland: Springer Nature. doi:10.1007/978-3-319-12385-1. ISBN   978-3-319-12384-4.
  8. ↑ "JUQ - Editorial Board" (PDF). SIAM. Retrieved 11 September 2023.
  9. ↑ "EPFL Doctorate Award". EPFL. Retrieved 11 September 2023.
  10. ↑ "A Calculus for the Optimal Quantification of Uncertainties | SIAM". pathlms.com.
  11. ↑ "(PDF) XVI International Conference on Hyperbolic Problems www ... · Scientifi c Committee Alberto Bressan (USA) · Gui-Qiang Chen (UK) · Camillo De Lellis (Switzerland) · Helge Holden". dokumen.tips.
  12. ↑ "Germund Dahlquist Prize". SIAM.
  13. ↑ "Class of 2022". www.siam.org.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.