Hessam Babaee

986 total citations
45 papers, 654 citations indexed

About

Hessam Babaee is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Hessam Babaee has authored 45 papers receiving a total of 654 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computational Mechanics, 18 papers in Statistical and Nonlinear Physics and 12 papers in Statistics, Probability and Uncertainty. Recurrent topics in Hessam Babaee's work include Model Reduction and Neural Networks (18 papers), Probabilistic and Robust Engineering Design (12 papers) and Fluid Dynamics and Turbulent Flows (9 papers). Hessam Babaee is often cited by papers focused on Model Reduction and Neural Networks (18 papers), Probabilistic and Robust Engineering Design (12 papers) and Fluid Dynamics and Turbulent Flows (9 papers). Hessam Babaee collaborates with scholars based in United States, Singapore and United Kingdom. Hessam Babaee's co-authors include George Em Karniadakis, Xuhui Meng, Chryssostomos Chryssostomidis, Sumanta Acharya, Themistoklis P. Sapsis, Xiaoliang Wan, Kaveh Laksari, Svein Kleiven, Peyman Givi and Mehmet Kurt and has published in prestigious journals such as Physical Review Letters, Journal of Fluid Mechanics and Journal of Computational Physics.

In The Last Decade

Hessam Babaee

45 papers receiving 638 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hessam Babaee United States 14 281 260 171 119 85 45 654
Christophe Prud'Homme France 13 533 1.9× 546 2.1× 249 1.5× 57 0.5× 22 0.3× 51 1.1k
Federico Negri Switzerland 8 766 2.7× 497 1.9× 321 1.9× 95 0.8× 35 0.4× 11 989
Daniele Venturi United States 17 474 1.7× 273 1.1× 399 2.3× 73 0.6× 91 1.1× 40 952
Kookjin Lee United States 9 302 1.1× 161 0.6× 88 0.5× 60 0.5× 72 0.8× 26 462
Rohit Tripathy United States 5 243 0.9× 89 0.3× 251 1.5× 47 0.4× 124 1.5× 7 584
Umberto Villa United States 15 104 0.4× 144 0.6× 143 0.8× 22 0.2× 90 1.1× 74 649
Bing Yu China 4 655 2.3× 293 1.1× 119 0.7× 67 0.6× 160 1.9× 9 848
Jean-Christophe Loiseau France 15 403 1.4× 473 1.8× 123 0.7× 170 1.4× 113 1.3× 26 903
Karen Veroy Germany 14 1.0k 3.7× 738 2.8× 457 2.7× 105 0.9× 25 0.3× 49 1.3k
Matthew J. Zahr United States 17 775 2.8× 570 2.2× 343 2.0× 132 1.1× 67 0.8× 45 1.1k

Countries citing papers authored by Hessam Babaee

Since Specialization
Citations

This map shows the geographic impact of Hessam Babaee'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 Hessam Babaee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hessam Babaee more than expected).

Fields of papers citing papers by Hessam Babaee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hessam Babaee. 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 Hessam Babaee. The network helps show where Hessam Babaee may publish in the future.

Co-authorship network of co-authors of Hessam Babaee

This figure shows the co-authorship network connecting the top 25 collaborators of Hessam Babaee. A scholar is included among the top collaborators of Hessam Babaee 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 Hessam Babaee. Hessam Babaee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Naderi, M. H., et al.. (2025). A cross algorithm for implicit time integration of random partial differential equations on low-rank matrix manifolds. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 481(2309). 1 indexed citations
2.
Babaee, Hessam, et al.. (2025). Optimally time-dependent modes of vortex gust–airfoil interactions. Journal of Fluid Mechanics. 1006. 4 indexed citations
3.
Babaee, Hessam, et al.. (2025). Accelerating high-fidelity simulations of chemically reacting flows using reduced-order modeling with time-dependent bases. Computer Methods in Applied Mechanics and Engineering. 437. 117758–117758. 1 indexed citations
4.
Babaee, Hessam, et al.. (2024). Time-dependent low-rank input–output operator for forced linearized dynamics with unsteady base flows. Journal of Fluid Mechanics. 1001. 4 indexed citations
5.
Laksari, Kaveh, et al.. (2024). Reconstructing blood flow in data-poor regimes: a vasculature network kernel for Gaussian process regression. Journal of The Royal Society Interface. 21(217). 20240194–20240194. 4 indexed citations
6.
Givi, Peyman, et al.. (2024). Reduced order modeling of turbulent reacting flows on low-rank matrix manifolds. Journal of Computational Physics. 521. 113549–113549. 1 indexed citations
7.
Ghahremani, Behzad & Hessam Babaee. (2024). A DEIM Tucker tensor cross algorithm and its application to dynamical low-rank approximation. Computer Methods in Applied Mechanics and Engineering. 423. 116879–116879. 6 indexed citations
8.
Givi, Peyman, et al.. (2024). Skeletal Kinetics Reduction for Astrophysical Reaction Networks. The Astrophysical Journal Supplement Series. 272(2). 34–34. 2 indexed citations
9.
Goswami, Somdatta, et al.. (2023). Learning stiff chemical kinetics using extended deep neural operators. Computer Methods in Applied Mechanics and Engineering. 419. 116674–116674. 31 indexed citations
10.
Meyer, Ryan M., et al.. (2023). Feature analysis acoustic signals for fiber-optic-sensing-based NDE for welded structures. 12–12. 1 indexed citations
11.
12.
Lubasch, Michael, Sergey Dolgov, Hessam Babaee, et al.. (2022). A quantum-inspired approach to exploit turbulence structures. Nature Computational Science. 2(1). 30–37. 59 indexed citations
13.
Toosizadeh, Nima, et al.. (2020). Low-Rank Representation of Head Impact Kinematics: A Data-Driven Emulator. Frontiers in Bioengineering and Biotechnology. 8. 555493–555493. 5 indexed citations
14.
Babaee, Hessam, et al.. (2020). Real-time reduced-order modeling of stochastic partial differential equations via time-dependent subspaces. Journal of Computational Physics. 415. 109511–109511. 22 indexed citations
15.
Raissi, Maziar, Hessam Babaee, & Peyman Givi. (2018). Deep Learning of PDF Turbulence Closure. Bulletin of the American Physical Society. 2 indexed citations
16.
Laksari, Kaveh, Mehmet Kurt, Hessam Babaee, Svein Kleiven, & David B. Camarillo. (2018). Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis. Physical Review Letters. 120(13). 138101–138101. 59 indexed citations
17.
Babaee, Hessam. (2017). A Data-Driven Low-Rank Approximation of Time-Dependent Stochastic Flows. Bulletin of the American Physical Society. 1 indexed citations
18.
Babaee, Hessam, et al.. (2017). A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems. Journal of Computational Physics. 344. 303–319. 30 indexed citations
19.
Babaee, Hessam, et al.. (2015). Feedback Stabilization of a Reduced-Order Model of a Jet in Crossflow. AIAA Journal. 53(9). 2472–2481. 7 indexed citations
20.
Babaee, Hessam & Sumanta Acharya. (2013). A Hybrid Staggered/Semistaggered Finite-Difference Algorithm for Solving Time-Dependent Incompressible Navier-Stokes Equations on Curvilinear Grids. Numerical Heat Transfer Part B Fundamentals. 65(1). 1–26. 8 indexed citations

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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