H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 35 Citations 6,917 139 World Ranking 3390 National Ranking 1313

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Statistics
  • Electrical engineering

Habib N. Najm mostly deals with Polynomial chaos, Uncertainty quantification, Applied mathematics, Mathematical optimization and Analytical chemistry. The concepts of his Polynomial chaos study are interwoven with issues in Stochastic process, Polynomial, Solver and Bayesian inference. Habib N. Najm combines subjects such as Projection method, Mathematical analysis, Galerkin method, Sensitivity analysis and Propagation of uncertainty with his study of Uncertainty quantification.

His Applied mathematics research is multidisciplinary, relying on both Projection, Flow, Representation, Probabilistic logic and Discretization. Many of his studies on Mathematical optimization involve topics that are commonly interrelated, such as Random variable. Habib N. Najm has researched Analytical chemistry in several fields, including Thermocouple and Work, Thermodynamics.

His most cited work include:

  • Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics (475 citations)
  • On the Adequacy of Certain Experimental Observables as Measurements of Flame Burning Rate (437 citations)
  • Uncertainty propagation using Wiener-Haar expansions (363 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Uncertainty quantification, Polynomial chaos, Mathematical optimization, Applied mathematics and Mechanics. His study focuses on the intersection of Uncertainty quantification and fields such as Probabilistic logic with connections in the field of Representation. His work deals with themes such as Stochastic process, Statistical physics, Galerkin method and Bayesian inference, which intersect with Polynomial chaos.

His Mathematical optimization research also works with subjects such as

  • Singular perturbation which intersects with area such as Ignition system,
  • Inverse problem most often made with reference to Markov chain Monte Carlo. By researching both Applied mathematics and Context, Habib N. Najm produces research that crosses academic boundaries. His study in the field of Flow and Microchannel also crosses realms of Flame structure and Laminar flame speed.

He most often published in these fields:

  • Uncertainty quantification (23.08%)
  • Polynomial chaos (21.63%)
  • Mathematical optimization (18.27%)

What were the highlights of his more recent work (between 2017-2021)?

  • Uncertainty quantification (23.08%)
  • Applied mathematics (17.79%)
  • Probabilistic logic (7.21%)

In recent papers he was focusing on the following fields of study:

Habib N. Najm mostly deals with Uncertainty quantification, Applied mathematics, Probabilistic logic, Statistical physics and Mathematical optimization. His Uncertainty quantification research incorporates elements of Helium and Surface. His work carried out in the field of Applied mathematics brings together such families of science as Tensor, Maxima and minima, Low-rank approximation, Rank and Polynomial chaos.

His Polynomial chaos research is included under the broader classification of Monte Carlo method. His Statistical physics study incorporates themes from Singular perturbation, Conditional random field, Anharmonicity, Propagation of uncertainty and Diagrammatic reasoning. His Duality study, which is part of a larger body of work in Mathematical optimization, is frequently linked to Diffusion map, bridging the gap between disciplines.

Between 2017 and 2021, his most popular works were:

  • Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence (58 citations)
  • TChem - A Software Toolkit for the Analysis of Complex Kinetic Models (27 citations)
  • Compressive sensing adaptation for polynomial chaos expansions (18 citations)

In his most recent research, the most cited papers focused on:

  • Quantum mechanics
  • Statistics
  • Electrical engineering

His main research concerns Probabilistic logic, Uncertainty quantification, Mathematical optimization, Software engineering and Applied mathematics. His Uncertainty quantification research includes elements of Rotation, Estimation theory, Convergence, Reduction and Bayesian inference. His Mathematical optimization research is multidisciplinary, incorporating perspectives in Reynolds-averaged Navier–Stokes equations, Probability density function and Turbulence kinetic energy.

Applied mathematics and First order are two areas of study in which Habib N. Najm engages in interdisciplinary work. His work investigates the relationship between Principle of maximum entropy and topics such as Hyperparameter that intersect with problems in Polynomial chaos. His Polynomial chaos study integrates concerns from other disciplines, such as Gaussian and Compressed sensing.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics

Habib N. Najm.
Annual Review of Fluid Mechanics (2009)

708 Citations

On the Adequacy of Certain Experimental Observables as Measurements of Flame Burning Rate

Habib N Najm;Phillip H Paul;Charles J Mueller;Peter S Wyckoff.
Combustion and Flame (1998)

690 Citations

Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes

Bert J. Debusschere;Habib N. Najm;Philippe P. Pébay;Omar M. Knio.
computational science and engineering (2005)

535 Citations

Uncertainty propagation using Wiener-Haar expansions

O. P. Le Maître;O. M. Knio;H. N. Najm;R. G. Ghanem.
Journal of Computational Physics (2004)

511 Citations

Stochastic spectral methods for efficient Bayesian solution of inverse problems

Youssef M. Marzouk;Habib N. Najm;Larry A. Rahn.
Journal of Computational Physics (2007)

472 Citations

A stochastic projection method for fluid flow. I: basic formulation

Olivier P. Le Maitre;Omar M. Kino;Habib N. Najm;Roger G. Ghanem.
Journal of Computational Physics (2001)

420 Citations

Multi-resolution analysis of wiener-type uncertainty propagation schemes

O. P. Le Maître;H. N. Najm;R. G. Ghanem;O. M. Knio.
Journal of Computational Physics (2004)

412 Citations

A stochastic projection method for fluid flow II.: random process

Olivier P. Le Maîetre;Matthew T. Reagan;Habib N. Najm;Roger G. Ghanem.
Journal of Computational Physics (2002)

391 Citations

Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

Youssef M. Marzouk;Habib N. Najm.
Journal of Computational Physics (2009)

386 Citations

Uncertainty quantification in reacting-flow simulations through non-intrusive spectral projection

Matthew T. Reagan;Habib N. Najm;Roger G. Ghanem;Omar M. Knio.
Combustion and Flame (2003)

345 Citations

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