Kevin Carlberg

2.8k total citations · 2 hit papers
33 papers, 1.7k citations indexed

About

Kevin Carlberg is a scholar working on Statistical and Nonlinear Physics, Statistics, Probability and Uncertainty and Computational Mechanics. According to data from OpenAlex, Kevin Carlberg has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistical and Nonlinear Physics, 18 papers in Statistics, Probability and Uncertainty and 13 papers in Computational Mechanics. Recurrent topics in Kevin Carlberg's work include Model Reduction and Neural Networks (33 papers), Probabilistic and Robust Engineering Design (18 papers) and Fluid Dynamics and Vibration Analysis (8 papers). Kevin Carlberg is often cited by papers focused on Model Reduction and Neural Networks (33 papers), Probabilistic and Robust Engineering Design (18 papers) and Fluid Dynamics and Vibration Analysis (8 papers). Kevin Carlberg collaborates with scholars based in United States, Canada and Russia. Kevin Carlberg's co-authors include Charbel Farhat, David Amsallem, Julien Cortial, Charbel Bou‐Mosleh, Youngsoo Choi, Louis J. Durlofsky, Eric Parish, Ray Tuminaro, Francesco Rizzi and Freddie Witherden and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and AIAA Journal.

In The Last Decade

Kevin Carlberg

33 papers receiving 1.7k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Efficient non‐linear model reduction via a least‐squares Petrov–Galerkin projection and compressive tensor approximations

2010 438 citations Kevin Carlberg, Charbel Farhat et al. International Journal for Numerical Methods in Engineering profile →
The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows

2013 411 citations Kevin Carlberg, Charbel Farhat et al. Journal of Computational Physics profile →

Peers

Countries citing papers authored by Kevin Carlberg

Since Specialization

Citations

This map shows the geographic impact of Kevin Carlberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kevin Carlberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Carlberg more than expected).

Fields of papers citing papers by Kevin Carlberg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin Carlberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kevin Carlberg. The network helps show where Kevin Carlberg may publish in the future.

Co-authorship network of co-authors of Kevin Carlberg

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Carlberg. A scholar is included among the top collaborators of Kevin Carlberg based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kevin Carlberg. Kevin Carlberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields 2023 ·Chang Yue, (unknown), Zhecheng Wang, (unknown), Kevin Carlberg, Eitan Grinspun	3
2	Model reduction for the material point method via an implicit neural representation of the deformation map 2023 ·Journal of Computational Physics ·(unknown), (unknown), Eitan Grinspun, Kevin Carlberg	6
3	Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws [Poster] 2021 ·OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) ·Kookjin Lee, Kevin Carlberg	2
4	Online adaptive basis refinement and compression for reduced-order models via vector-space sieving 2020 ·Computer Methods in Applied Mechanics and Engineering ·(unknown), Kevin Carlberg	19
5	Time-series machine-learning error models for approximate solutions to parameterized dynamical systems 2020 ·Computer Methods in Applied Mechanics and Engineering ·Eric Parish, Kevin Carlberg	24
6	Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction 2020 ·AIAA Scitech 2020 Forum ·Patrick Blonigan, Kevin Carlberg, Francesco Rizzi, (unknown), (unknown)	10
7	Propagating uncertainties in large-scale hemodynamics models via network uncertainty quantification and reduced-order modeling 2019 ·Computer Methods in Applied Mechanics and Engineering ·(unknown), (unknown), Pablo J. Blanco, Kevin Carlberg, Alessandro Veneziani	19
8	Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations 2019 ·Computer Methods in Applied Mechanics and Engineering ·(unknown), Kevin Carlberg	25
9	Online adaptive basis refinement and compression for reduced-order models. 2019 ·arXiv (Cornell University) ·(unknown), Kevin Carlberg	2
10	Space--Time Least-Squares Petrov--Galerkin Projection for Nonlinear Model Reduction 2019 ·SIAM Journal on Scientific Computing ·Youngsoo Choi, Kevin Carlberg	51
11	Error estimation for surrogate models of dynamical systems using machine learning. 2017 ·arXiv (Cornell University) ·(unknown), Kevin Carlberg, Louis J. Durlofsky	4
12	Error modeling for surrogates of dynamical systems using machine learning 2017 ·International Journal for Numerical Methods in Engineering ·(unknown), Kevin Carlberg, Louis J. Durlofsky	47
13	Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method 2016 ·SIAM Journal on Matrix Analysis and Applications ·Kevin Carlberg, (unknown), Ray Tuminaro	17
14	Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting 2015 ·Computer Methods in Applied Mechanics and Engineering ·Kevin Carlberg, Jaideep Ray, Bart van Bloemen Waanders	11
15	Adaptive h‐refinement for reduced‐order models 2014 ·International Journal for Numerical Methods in Engineering ·Kevin Carlberg	88
16	Efficient structure-preserving model reduction for nonlinear mechanical systems with application to structural dynamics 2012 ·Kevin Carlberg, Ray Tuminaro, Paul T. Boggs	9
17	The GNAT nonlinear model reduction method and its application to fluid dynamics problems 2011 ·Kevin Carlberg, David Amsallem, (unknown), Matthew J. Zahr, Charbel Farhat	20
18	A low‐cost, goal‐oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems 2010 ·International Journal for Numerical Methods in Engineering ·Kevin Carlberg, Charbel Farhat	80
19	An On-Line Method for Interpolating Linear Reduced-Order Structural Dynamics Models 2009 ·50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference ·David Amsallem, Julien Cortial, Charbel Farhat, Kevin Carlberg	1
20	A method for interpolating on manifolds structural dynamics reduced‐order models 2009 ·International Journal for Numerical Methods in Engineering ·David Amsallem, Julien Cortial, Kevin Carlberg, Charbel Farhat	176

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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