Adrian Nachman

3.8k total citations · 1 hit paper
48 papers, 2.2k citations indexed

About

Adrian Nachman is a scholar working on Electrical and Electronic Engineering, Mathematical Physics and Biomedical Engineering. According to data from OpenAlex, Adrian Nachman has authored 48 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 20 papers in Mathematical Physics and 18 papers in Biomedical Engineering. Recurrent topics in Adrian Nachman's work include Electrical and Bioimpedance Tomography (19 papers), Numerical methods in inverse problems (17 papers) and Advanced Mathematical Modeling in Engineering (9 papers). Adrian Nachman is often cited by papers focused on Electrical and Bioimpedance Tomography (19 papers), Numerical methods in inverse problems (17 papers) and Advanced Mathematical Modeling in Engineering (9 papers). Adrian Nachman collaborates with scholars based in Canada, United States and Taiwan. Adrian Nachman's co-authors include Robert C. Waag, Mark J. Ablowitz, James F. Smith, T. Douglas Mast, Victor Isakov, Alexandru Tamasan, Günther Uhlmann, John Sylvester, José Zariffa and Makoto Tabei and has published in prestigious journals such as Scientific Reports, The Journal of the Acoustical Society of America and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Adrian Nachman

47 papers receiving 1.9k citations

Hit Papers

Global Uniqueness for a Two-Dimensional Inverse Boundary ... 1996 2026 2006 2016 1996 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adrian Nachman Canada 23 1.3k 953 685 597 554 48 2.2k
John Sylvester United States 23 2.0k 1.5× 924 1.0× 560 0.8× 679 1.1× 1.0k 1.8× 44 2.4k
Hyeonbae Kang South Korea 34 1.8k 1.4× 1.2k 1.3× 626 0.9× 1.6k 2.7× 1.2k 2.2× 151 3.6k
George Dassios Greece 24 617 0.5× 629 0.7× 277 0.4× 624 1.0× 211 0.4× 165 1.9k
Joyce R. McLaughlin United States 25 1.0k 0.8× 601 0.6× 143 0.2× 423 0.7× 553 1.0× 67 2.0k
Michael Vogelius United States 36 2.3k 1.8× 961 1.0× 1.3k 1.8× 2.1k 3.6× 2.1k 3.8× 91 4.9k
Houssem Haddar France 29 1.8k 1.4× 1.3k 1.4× 398 0.6× 897 1.5× 602 1.1× 124 2.5k
Liliana Borcea United States 19 560 0.4× 870 0.9× 656 1.0× 499 0.8× 148 0.3× 67 1.8k
Thomas Schuster Germany 19 766 0.6× 431 0.5× 263 0.4× 215 0.4× 249 0.4× 72 1.4k
David C. Dobson United States 20 396 0.3× 381 0.4× 628 0.9× 237 0.4× 146 0.3× 40 1.6k
Andreas Rieder Germany 20 526 0.4× 257 0.3× 277 0.4× 140 0.2× 94 0.2× 63 1.1k

Countries citing papers authored by Adrian Nachman

Since Specialization
Citations

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

Fields of papers citing papers by Adrian Nachman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adrian Nachman

This figure shows the co-authorship network connecting the top 25 collaborators of Adrian Nachman. A scholar is included among the top collaborators of Adrian Nachman 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 Adrian Nachman. Adrian Nachman 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.
Nachman, Adrian, et al.. (2024). An Optimal Transport Analogue of the Rudin–Osher–Fatemi Model and Its Corresponding Multiscale Theory. SIAM Journal on Mathematical Analysis. 56(1). 1114–1148.
2.
Nachman, Adrian, et al.. (2020). Determining a Riemannian metric from minimal areas. Advances in Mathematics. 366. 107025–107025. 9 indexed citations
3.
Balas, Michael, et al.. (2019). Selective peripheral nerve recordings from nerve cuff electrodes using convolutional neural networks. Journal of Neural Engineering. 17(1). 16042–16042. 34 indexed citations
4.
Nachman, Adrian, et al.. (2019). Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings. Scientific Reports. 9(1). 11145–11145. 27 indexed citations
6.
Nachman, Adrian, et al.. (2016). Use of spatiotemporal templates for pathway discrimination in peripheral nerve recordings: a simulation study. Journal of Neural Engineering. 14(1). 16013–16013. 21 indexed citations
7.
Radau, Perry, et al.. (2015). Multiscale properties of weighted total variation flow with applications to denoising and registration. Medical Image Analysis. 23(1). 28–42. 10 indexed citations
8.
Nachman, Adrian, et al.. (2013). Experimental implementation of a new method of imaging anisotropic electric conductivities. PubMed. 2013. 6437–6440. 10 indexed citations
9.
Wang, Dinghui, et al.. (2010). Radio-Frequency Current Density Imaging Based on a 180$^\circ$ Sample Rotation With Feasibility Study of Full Current Density Vector Reconstruction. IEEE Transactions on Medical Imaging. 30(2). 327–337. 2 indexed citations
10.
Wang, Dinghui, et al.. (2009). Multislice Radio-Frequency Current Density Imaging. IEEE Transactions on Medical Imaging. 28(7). 1083–1092. 8 indexed citations
11.
T., Ann, et al.. (2008). Current Density Impedance Imaging. IEEE Transactions on Medical Imaging. 27(9). 1301–1309. 34 indexed citations
12.
Nachman, Adrian, et al.. (2007). On imaging obstacles inside inhomogeneous media. Journal of Functional Analysis. 252(2). 490–516. 36 indexed citations
13.
T., Ann, et al.. (2005). A new approach to current density impedance imaging. PubMed. 3. 1321–1324. 23 indexed citations
14.
Mast, T. Douglas, et al.. (2001). A k-space method for large-scale models of wave propagation in tissue. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control. 48(2). 341–354. 130 indexed citations
15.
Nachman, Adrian. (1996). Global Uniqueness for a Two-Dimensional Inverse Boundary Value Problem. Annals of Mathematics. 143(1). 71–71. 510 indexed citations breakdown →
16.
Isakov, Victor & Adrian Nachman. (1995). Global uniqueness for a two-dimensional semilinear elliptic inverse problem. Transactions of the American Mathematical Society. 347(9). 3375–3390. 77 indexed citations
17.
Isakov, Victor & Adrian Nachman. (1995). Global Uniqueness for a Two-Dimensional Semilinear Elliptic Inverse Problem. Transactions of the American Mathematical Society. 347(9). 3375–3375. 22 indexed citations
18.
Nachman, Adrian, James F. Smith, & Robert C. Waag. (1990). An equation for acoustic propagation in inhomogeneous media with relaxation losses. The Journal of the Acoustical Society of America. 88(3). 1584–1595. 90 indexed citations
19.
Nachman, Adrian, et al.. (1989). A new method for specifying nonradiating, monochromatic, scalar sources and their fields. Journal of the Optical Society of America A. 6(9). 1388–1388. 30 indexed citations
20.
Nachman, Adrian. (1988). Reconstructions From Boundary Measurements. Annals of Mathematics. 128(3). 531–531. 385 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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