Noémi Petra

656 total citations
21 papers, 384 citations indexed

About

Noémi Petra is a scholar working on Atmospheric Science, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Noémi Petra has authored 21 papers receiving a total of 384 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Atmospheric Science, 5 papers in Statistics, Probability and Uncertainty and 4 papers in Artificial Intelligence. Recurrent topics in Noémi Petra's work include Probabilistic and Robust Engineering Design (5 papers), Gaussian Processes and Bayesian Inference (4 papers) and Spectroscopy and Laser Applications (4 papers). Noémi Petra is often cited by papers focused on Probabilistic and Robust Engineering Design (5 papers), Gaussian Processes and Bayesian Inference (4 papers) and Spectroscopy and Laser Applications (4 papers). Noémi Petra collaborates with scholars based in United States and New Zealand. Noémi Petra's co-authors include Omar Ghattas, Umberto Villa, Georg Stadler, Tobin Isaac, J. Zweck, Susan E. Minkoff, A.A. Kosterev, David Thomazy, Omar Ghattas and Michael Gurnis and has published in prestigious journals such as Journal of Computational Physics, SIAM Journal on Scientific Computing and Physics of The Earth and Planetary Interiors.

In The Last Decade

Noémi Petra

19 papers receiving 369 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Noémi Petra United States 8 131 103 81 65 64 21 384
J. Schoendorf United States 14 66 0.5× 20 0.2× 196 2.4× 21 0.3× 15 0.2× 24 865
Nicolai Nygaard Denmark 18 97 0.7× 38 0.4× 8 0.1× 73 1.1× 22 0.3× 34 819
Astrid Jourdan France 10 51 0.4× 45 0.4× 55 0.7× 44 0.7× 30 0.5× 25 353
Susan E. Minkoff United States 17 79 0.6× 110 1.1× 4 0.0× 33 0.5× 58 0.9× 49 1.1k
Bert W. Rust United States 9 32 0.2× 10 0.1× 14 0.2× 19 0.3× 49 0.8× 21 307
Patrick Fischer France 12 80 0.6× 12 0.1× 5 0.1× 12 0.2× 51 0.8× 43 465
Xianyi Wang China 13 147 1.1× 7 0.1× 24 0.3× 17 0.3× 29 0.5× 89 646
D.M. Webber United Kingdom 14 58 0.4× 5 0.0× 39 0.5× 10 0.2× 63 1.0× 36 476
R. H. Tolson United States 19 144 1.1× 8 0.1× 14 0.2× 19 0.3× 61 1.0× 94 1.1k
Kenneth D. Jarman United States 14 5 0.0× 59 0.6× 46 0.6× 66 1.0× 41 0.6× 34 415

Countries citing papers authored by Noémi Petra

Since Specialization
Citations

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

Fields of papers citing papers by Noémi Petra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noémi Petra

This figure shows the co-authorship network connecting the top 25 collaborators of Noémi Petra. A scholar is included among the top collaborators of Noémi Petra 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 Noémi Petra. Noémi Petra 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.
Romero, Ignacio, Roummel F. Marcia, Ignacio Aravena, & Noémi Petra. (2025). Optimal PMU Placement for State Estimation with Grid Parameter Uncertainty. 1–5.
2.
Petra, Noémi, et al.. (2024). Point Spread Function Approximation of High-Rank Hessians with Locally Supported Nonnegative Integral Kernels. SIAM Journal on Scientific Computing. 46(3). A1658–A1689. 1 indexed citations
3.
Alexanderian, Alen, et al.. (2024). Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty. Inverse Problems. 40(9). 95001–95001. 5 indexed citations
4.
5.
Stadler, Georg, et al.. (2023). Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization. Inverse Problems. 39(8). 85006–85006. 2 indexed citations
6.
Petra, Noémi, et al.. (2023). On global normal linear approximations for nonlinear Bayesian inverse problems. Inverse Problems. 39(5). 54001–54001. 5 indexed citations
7.
Petra, Cosmin G., et al.. (2022). On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations. Optimization methods & software. 38(1). 59–90. 1 indexed citations
8.
Villa, Umberto, et al.. (2021). Inferring the basal sliding coefficient field for the Stokes ice sheet model under rheological uncertainty. ˜The œcryosphere. 15(4). 1731–1750. 16 indexed citations
9.
Villa, Umberto, Noémi Petra, & Omar Ghattas. (2021). hIPPYlib. ACM Transactions on Mathematical Software. 47(2). 1–34. 53 indexed citations
10.
Petra, Noémi, Umberto Villa, & Omar Ghattas. (2020). hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs. AGU Fall Meeting Abstracts. 2020. 2 indexed citations
11.
Petra, Noémi, et al.. (2020). Linearized Bayesian inference for Young’s modulus parameter field in an elastic model of slender structures. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 476(2238). 20190476–20190476. 4 indexed citations
12.
Petra, Cosmin G., et al.. (2020). On the Derivation of Quasi-Newton Formulas for Optimization in Function Spaces. Numerical Functional Analysis and Optimization. 41(13). 1564–1587. 8 indexed citations
13.
Villa, Umberto, Noémi Petra, & Omar Ghattas. (2018). hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems. The Journal of Open Source Software. 3(30). 940–940. 37 indexed citations
14.
Zhu, Hongyu, Noémi Petra, Georg Stadler, et al.. (2016). Inversion of geothermal heat flux in a thermomechanically coupled nonlinear Stokes ice sheet model. ˜The œcryosphere. 10(4). 1477–1494. 7 indexed citations
15.
Isaac, Tobin, Noémi Petra, Georg Stadler, & Omar Ghattas. (2015). Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet. Journal of Computational Physics. 296. 348–368. 99 indexed citations
16.
Stadler, Georg, et al.. (2014). Towards adjoint-based inversion for rheological parameters in nonlinear viscous mantle flow. Physics of The Earth and Planetary Interiors. 234. 23–34. 30 indexed citations
17.
Petra, Noémi, J. Zweck, Susan E. Minkoff, Anatoliy A. Kosterev, & James H. Doty. (2011). Modeling and Design Optimization of a Resonant Optothermoacoustic Trace Gas Sensor. SIAM Journal on Applied Mathematics. 71(1). 309–332. 14 indexed citations
18.
Petra, Noémi, et al.. (2011). Validation of a Model of a Resonant Optothermoacoustic Trace Gas Sensor. Maryland Shared Open Access Repository (USMAI Consortium). 27. JTuI115–JTuI115. 1 indexed citations
19.
Petra, Noémi, et al.. (2010). Numerical and Experimental Investigation for a Resonant Optothermoacoustic Sensor. Maryland Shared Open Access Repository (USMAI Consortium). 27. CMJ6–CMJ6. 4 indexed citations
20.
Petra, Noémi, J. Zweck, A.A. Kosterev, Susan E. Minkoff, & David Thomazy. (2009). Theoretical analysis of a quartz-enhanced photoacoustic spectroscopy sensor. Applied Physics B. 94(4). 673–680. 94 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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