Publications

Vijay Veerabadran, Fanyi Xiao, Nitin Kamra, Pedro Matias, Joy Chen, Caley Drooff, Brett D Roads, Riley Williams, Ethan Henderson, Xuanyi Zhao, Kevin Carlberg, Joseph Tighe, Karl Ridgeway (2025). Benchmarking egocentric multimodal goal inference for assistive wearable agents. NeurIPS 2025 Datasets and Benchmarks Track (Spotlight).

Yuxuan Sun, Manchen Wang, Shengyi Qian, William R Wong, Eric Gan, Pierluca D'Oro, Alejandro Castillejo Munoz, Sneha Silwal, Pedro Matias, Nitin Kamra, Kevin Carlberg, et al. (2025). DigiData: Training and evaluating general-purpose mobile control agents. arXiv:2511.07413.

J Nathan Kutz, Peter Battaglia, Michael Brenner, Kevin Carlberg, Aric Hagberg, Shirley Ho, Stephan Hoyer, Henning Lange, Hod Lipson, Michael W Mahoney, et al. (2025). Accelerating scientific discovery with the common task framework. arXiv:2511.04001.

Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Carlberg, Neil Walton, Kody JH Law (2024). Accelerating look-ahead in Bayesian optimization: Multilevel Monte Carlo is all you need. arXiv:2402.02111.

Zeshun Zong, Xuan Li, Minchen Li, Maurizio Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Chen (2023). Neural stress fields for reduced-order elastoplasticity and fracture. SIGGRAPH Asia 2023.

Yutong Chang, Peter Chen, Zeyu Wang, Maurizio Chiaramonte, Kevin Carlberg, Eitan Grinspun (2023). LiCROM: Linear-subspace continuous reduced order modeling with neural fields. SIGGRAPH Asia 2023.

Peter Chen, Jinxu Xiang, Dong Heon Cho, Yue Chang, G A Pershing, Henrique Maia, Maurizio Chiaramonte, Kevin Carlberg, Eitan Grinspun (2023). CROM: Continuous reduced-order modeling of PDEs using implicit neural representations. ICLR 2023 (Notable top 25%).

Peter Chen, Maurizio Chiaramonte, Eitan Grinspun, Kevin Carlberg (2023). Model reduction for the material point method via an implicit neural representation of the deformation map. Journal of Computational Physics, 478:111908, 2023.

Preprint PDF DOI

Steven Rodriguez, Athanasios Iliopoulos, Kevin Carlberg, Steven Brunton, John Steuben, John Michopoulos (2022). Projection-tree reduced-order modeling for fast n-body computations. Journal of Computational Physics, 459:111141, 2022.

Preprint PDF DOI

Payton Lindsay, Jason Fike, Irina Tezaur, Kevin Carlberg (2022). Preconditioned least-squares Petrov–Galerkin reduced order models. International Journal for Numerical Methods in Engineering, 123(20):4809–4843, 2022.

Preprint PDF DOI

Stefano Pagani, Andrea Manzoni, Kevin Carlberg (2022). Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. International Journal for Uncertainty Quantification, 12(1), 2022.

Chi Hoang, Youngsoo Choi, Kevin Carlberg (2021). Domain-decomposition least-squares Petrov–Galerkin (DD-LSPG) nonlinear model reduction. Computer Methods in Applied Mechanics and Engineering, 384:113997, 2021.

Preprint PDF DOI

Alexander Schein, Kevin Carlberg, Matthew Zahr (2021). Preserving general physical properties in model reduction of dynamical systems via constrained-optimization projection. International Journal for Numerical Methods in Engineering, 122(14):3368–3399, 2021.

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Patrick Blonigan, Francesco Rizzi, Matthew Howard, Jason Fike, Kevin Carlberg (2021). Model reduction for steady hypersonic aerodynamics via conservative manifold least-squares Petrov–Galerkin projection. AIAA Journal, 59(4):1296–1312, 2021.

Eric Parish, Kevin Carlberg (2021). Windowed least-squares model reduction for dynamical systems. Journal of Computational Physics, 426:109939, 2021.

Kookjin Lee, Kevin Carlberg (2021). Deep Conservation: A latent dynamics model for exact satisfaction of physical conservation laws. AAAI 2021.

Eric Parish, Kevin Carlberg (2020). Time-series machine-learning error models for approximate solutions to parameterized dynamical systems. Computer Methods in Applied Mechanics and Engineering, 365:112990, 2020..

Philip Etter, Kevin Carlberg (2020). Online adaptive basis refinement and compression for reduced-order models via vector-space sieving. Computer Methods in Applied Mechanics and Engineering, 364:112931, 2020.

Francesco Rizzi, Patrick Blonigan, Kevin Carlberg (2020). Pressio: Enabling projection-based model reduction for large-scale nonlinear dynamical systems. arXiv:2003.07798.

Preprint Code Project

Patrick Blonigan, Kevin Carlberg, Francesco Rizzi, Micah Howard, Jeff Fike (2020). Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction. AIAA Paper 2020-0104, AIAA Scitech 2020 Forum, Orlando, FL, January 6–10, 2020.

Kookjin Lee, Kevin Carlberg (2020). Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders. Journal of Computational Physics, Vol. 404, p. 108973 (2020).

Preprint PDF Slides

Eric Parish, Kevin Carlberg (2019). Windowed least-squares model reduction for dynamical systems.

Kevin Carlberg, Sofia Guzzetti, Mohammad Khalil, Khachik Sargsyan (2019). The network uncertainty quantification method for propagating uncertainties in component-based systems. Submitted to JUQ.

Matthew Zahr, Kevin Carlberg, Drew Kouri (2019). An efficient, globally convergent method for optimization under uncertainty using adaptive model reduction and sparse grids. SIAM/ASA Journal on Uncertainty Quantification, Vol. 7, No. 3, p.877–912 (2019).

Kevin Carlberg, Antony Jameson, Mykel Kochenderfer, Jeremy Morton, Liqian Peng, Freddie Witherden (2019). Recovering missing CFD data for high-order discretizations using deep neural networks and dynamics learning. Journal of Computational Physics, Vol. 395, p. 105–124 (2019).

Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth (2019). Data-driven time parallelism via forecasting. SIAM Journal on Scientific Computing, 41(3):B466–B496, 2019.

Preprint PDF Slides

Brian Freno, Kevin Carlberg (2019). Machine-learning error models for approximate solutions to parameterized systems of nonlinear equations. Computer Methods in Applied Mechanics and Engineering, Vol. 348, p.250–296 (2019).

Stefano Pagani, Andrea Manzoni, Kevin Carlberg (2019). Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. Submitted to SIAM JUQ.

Youngsoo Choi, Kevin Carlberg (2019). Space–time least-squares Petrov–Galerkin projection for nonlinear model reduction. SIAM Journal on Scientific Computing, Vol. 41, No. 1, p. A26–A58 (2019).

Preprint PDF Slides

Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan (2018). Conservative model reduction for finite-volume models. Journal of Computational Physics, Vol. 371, p. 280–314 (2018).

Preprint PDF Slides Video

Kookjin Lee, Kevin Carlberg, Howard Elman (2018). Stochastic least-squares Petrov–Galerkin method for parameterized linear systems. SIAM/ASA Journal on Uncertainty Quantification, Vol. 6, No. 1, p.374–396 (2018).

Kevin Carlberg, Virginia Forstall, Ray Tuminaro (2017). Krylov-subspace recycling via the POD-augmented conjugate-gradient method. SIAM Journal on Matrix Analysis and Applications, Vol. 37, No. 3, p.1304–1336 (2016).

Preprint PDF Video

John Tencer, Kevin Carlberg, Marvin Larsen, Roy Hogan (2017). Accelerated solution of discrete ordinates approximation to the Boltzmann transport equation via model reduction. Journal of Heat Transfer, Vol. 139, No. 12, p.122701 (2017).

Sumeet Trehan, Kevin Carlberg, Louis Durlofsky (2017). Error modeling for surrogates of dynamical systems using machine learning. International Journal for Numerical Methods in Engineering, Vol. 112, No. 12, p. 1801–1827 (2017).

Liqian Peng, Kevin Carlberg (2017). Structure-preserving model reduction for marginally stable LTI systems. Preprint.

Kevin Carlberg, Matthew Barone, Harbir Antil (2017). Galerkin v. least-squares Petrov--Galerkin projection in nonlinear model reduction. Journal of Computational Physics, Vol. 330, p. 693–734 (2017).

Preprint PDF Video

John Tencer, Kevin Carlberg, Marvin Larsen, Roy Hogan (2016). Reduced order modeling applied to the discrete ordinates method for radiation heat transfer in participating media. HT 2016-7010, ASME 2016 Summer Heat Transfer Conference, Washington, DC, July 10–14, 2016.

Kevin Carlberg, Jaideep Ray, Bart van Bloemen Waanders (2015). Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting. Computer Methods in Applied Mechanics and Engineering, Vol. 289, p.79–103 (2015).

Kevin Carlberg (2015). Adaptive $h$-refinement for reduced-order models. International Journal for Numerical Methods in Engineering, Vol. 102, No. 5, p.1192–1210 (2015).

Preprint PDF Video

Kevin Carlberg, Ray Tuminaro, Paul Boggs (2015). Preserving Lagrangian structure in nonlinear model reduction with application to structural dynamics. SIAM Journal on Scientific Computing, Vol. 37, No. 2, p. B153–B184 (2015).

Martin Drohmann, Kevin Carlberg (2015). The ROMES method for statistical modeling of reduced-order-model error. SIAM/ASA Journal on Uncertainty Quantification, Vol. 3, No. 1, p.116–145 (2015).

Kevin Carlberg, Charbel Farhat, Julien Cortial, David Amsallem (2013). The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows. Journal of Computational Physics, Vol. 242, p. 623–647 (2013).

Preprint PDF Video

Kevin Carlberg, Ray Tuminaro, Paul Boggs (2012). Efficient structure-preserving model reduction for nonlinear mechanical systems with application to structural dynamics. AIAA Paper 2012-1969, 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, Hawaii, April 23–26, 2012.

Kevin Carlberg, Julien Cortial, David Amsallem, Matthew Zahr, Charbel Farhat (2011). The GNAT nonlinear model reduction method and its application to fluid dynamics problems. AIAA Paper 2011-3112, 6th AIAA Theoretical Fluid Mechanics Conference, Honolulu, Hawaii, June 27–30, 2011.

Kevin Carlberg, Charbel Farhat (2011). A low-cost, goal-oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems. International Journal for Numerical Methods in Engineering, Vol. 86, No. 3, p. 381–402 (2011).

Kevin Carlberg, Charbel Bou-Mosleh, Charbel Farhat (2011). Efficient non-linear model reduction via a least-squares Petrov–Galerkin projection and compressive tensor approximations. International Journal for Numerical Methods in Engineering, Vol. 86, No. 2, p. 155–181 (2011).

Robert Stephan, Kevin Carlberg (2010). Gappy data reconstruction and applications in archaeology. Proceedings of XXXVIII Conference on Computer Applications & Quantitative Methods in Archaeology, Granada, Spain, April 6–9, 2010.

David Amsallem, Julien Cortial, Kevin Carlberg, Charbel Farhat (2009). A method for interpolating on manifolds structural dynamics reduced-order models. International Journal for Numerical Methods in Engineering, Vol. 80, No. 9, p. 1241–1257 (2009).

Kevin Carlberg, Charbel Farhat (2009). An adaptive POD-Krylov reduced-order model for structural optimization. Proceedings of 8th World Congress on Structural and Multidisciplinary Optimization, Lisbon, Portugal, June 1–5, 2009.

Kevin Carlberg, Charbel Farhat (2008). A low-cost, goal-oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems. AIAA Paper 2008-5964, 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Victoria, Canada, September 10–12, 2008.