Daniela Calvetti

5.5k total citations
178 papers, 3.8k citations indexed

About

Daniela Calvetti is a scholar working on Computational Theory and Mathematics, Computational Mechanics and Mathematical Physics. According to data from OpenAlex, Daniela Calvetti has authored 178 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Computational Theory and Mathematics, 41 papers in Computational Mechanics and 38 papers in Mathematical Physics. Recurrent topics in Daniela Calvetti's work include Matrix Theory and Algorithms (45 papers), Numerical methods in inverse problems (38 papers) and Sparse and Compressive Sensing Techniques (26 papers). Daniela Calvetti is often cited by papers focused on Matrix Theory and Algorithms (45 papers), Numerical methods in inverse problems (38 papers) and Sparse and Compressive Sensing Techniques (26 papers). Daniela Calvetti collaborates with scholars based in United States, Italy and Finland. Daniela Calvetti's co-authors include Lothar Reichel, Erkki Somersalo, Fiorella Sgallari, Bryan W. Lewis, Serena Morigi, Gene H. Golub, James Baglama, Rossana Occhipinti, William B. Gragg and Jari P. Kaipio and has published in prestigious journals such as Journal of Neurophysiology, Journal of Computational Physics and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Daniela Calvetti

173 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniela Calvetti United States 32 989 781 775 481 479 178 3.8k
James G. Nagy United States 26 368 0.4× 905 1.2× 729 0.9× 281 0.6× 445 0.9× 107 2.5k
Dianne P. O’Leary United States 36 1.7k 1.7× 1.7k 2.1× 1.3k 1.6× 918 1.9× 1.0k 2.1× 169 8.4k
William W. Symes United States 40 485 0.5× 574 0.7× 694 0.9× 194 0.4× 337 0.7× 204 7.1k
Tryphon T. Georgiou United States 42 607 0.6× 464 0.6× 266 0.3× 134 0.3× 241 0.5× 225 5.3k
C. W. Groetsch United States 19 570 0.6× 406 0.5× 1.2k 1.6× 163 0.3× 393 0.8× 73 2.6k
Fadil Santosa United States 28 688 0.7× 697 0.9× 1.1k 1.5× 305 0.6× 784 1.6× 102 3.9k
Heinz W. Engl Austria 26 1.1k 1.1× 1.2k 1.6× 3.4k 4.4× 272 0.6× 1.0k 2.1× 88 5.9k
Alfred K. Louis Germany 28 351 0.4× 430 0.6× 1.1k 1.4× 134 0.3× 790 1.6× 99 2.7k
Martin Burger Germany 40 938 0.9× 2.2k 2.8× 1.3k 1.6× 207 0.4× 1.1k 2.3× 215 7.2k
А. Г. Рамм United States 26 1.1k 1.1× 203 0.3× 2.5k 3.2× 810 1.7× 1.1k 2.2× 421 3.8k

Countries citing papers authored by Daniela Calvetti

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Calvetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela Calvetti

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela Calvetti. A scholar is included among the top collaborators of Daniela Calvetti 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 Daniela Calvetti. Daniela Calvetti 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.
Somersalo, Erkki, et al.. (2025). A Bayesian approach to locally varying regularization in optical flow velocimetry. Physics of Fluids. 37(5). 1 indexed citations
2.
Calvetti, Daniela & Erkki Somersalo. (2025). Distributed Tikhonov regularization for ill-posed inverse problems from a Bayesian perspective. Computational Optimization and Applications. 91(2). 541–572. 1 indexed citations
3.
Calvetti, Daniela, et al.. (2024). Myobolica: A Stochastic Approach to Estimate Physiological Muscle Control Variability. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 3270–3277.
4.
Calvetti, Daniela, et al.. (2024). Adaptive anisotropic Bayesian meshing for inverse problems. Inverse Problems. 40(4). 45008–45008.
5.
Calvetti, Daniela, et al.. (2024). Exploring muscle recruitment by Bayesian methods during motion. Chaos Solitons & Fractals. 185. 115082–115082. 1 indexed citations
6.
Calvetti, Daniela & Erkki Somersalo. (2023). Bayesian Scientific Computing. Applied mathematical sciences. 5 indexed citations
7.
Calvetti, Daniela & Erkki Somersalo. (2023). Post-pandemic modeling of COVID-19: Waning immunity determines recurrence frequency. Mathematical Biosciences. 365. 109067–109067. 7 indexed citations
8.
Somersalo, Erkki, et al.. (2023). A spatially distributed model of brain metabolism highlights the role of diffusion in brain energy metabolism. Journal of Theoretical Biology. 572. 111567–111567. 4 indexed citations
9.
Calvetti, Daniela, et al.. (2022). Bayesian hierarchical dictionary learning. Inverse Problems. 39(2). 24006–24006. 1 indexed citations
10.
Calvetti, Daniela, Alexander Hoover, Johnie Rose, & Erkki Somersalo. (2021). Bayesian particle filter algorithm for learning epidemic dynamics. Inverse Problems. 37(11). 115008–115008. 11 indexed citations
11.
Calvetti, Daniela, Alexander Hoover, Johnie Rose, & Erkki Somersalo. (2021). Modeling Epidemic Spread among a Commuting Population Using Transport Schemes. Mathematics. 9(16). 1861–1861. 2 indexed citations
12.
Calvetti, Daniela, et al.. (2020). Sparsity promoting hybrid solvers for hierarchical bayesian inverse problems. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 19 indexed citations
13.
Calvetti, Daniela, et al.. (2020). A Bayesian filtering approach to layer stripping for electrical impedance tomography. Inverse Problems. 36(5). 55014–55014. 5 indexed citations
14.
Calvetti, Daniela, et al.. (2019). Sparse reconstructions from few noisy data: analysis of hierarchical Bayesian models with generalized gamma hyperpriors. Inverse Problems. 36(2). 25010–25010. 27 indexed citations
15.
Gerardo‐Giorda, Luca, et al.. (2019). Brain energetics plays a key role in the coordination of electrophysiology, metabolism and hemodynamics: Evidence from an integrated computational model. Journal of Theoretical Biology. 478. 26–39. 6 indexed citations
16.
Calvetti, Daniela, Jari P. Kaipio, & Erkki Somersalo. (2006). Aristotelian prior boundary conditions. 1. 63–81. 34 indexed citations
17.
Calvetti, Daniela, Per Christian Hansen, & Lothar Reichel. (2001). L-Curve Curvature Bounds via Lanczos Bidiagonalization. ETNA - Electronic Transactions on Numerical Analysis. 14. 134–149. 36 indexed citations
18.
Calvetti, Daniela. (1992). A stochastic roundoff error analysis for the convolution. Mathematics of Computation. 59(200). 569–582. 1 indexed citations
19.
Calvetti, Daniela. (1991). A stochastic roundoff error analysis for the fast Fourier transform. Mathematics of Computation. 56(194). 755–774. 19 indexed citations
20.
Calvetti, Daniela. (1991). A Stochastic Roundoff Error Analysis for the Fast Fourier Transform. Mathematics of Computation. 56(194). 755–755. 4 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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