John de Pillis

42 total papers · 475 total citations
30 papers, 361 citations indexed

About

John de Pillis is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Statistical and Nonlinear Physics. According to data from OpenAlex, John de Pillis has authored 30 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computational Theory and Mathematics, 13 papers in Numerical Analysis and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in John de Pillis's work include Matrix Theory and Algorithms (23 papers), Advanced Optimization Algorithms Research (11 papers) and Iterative Methods for Nonlinear Equations (5 papers). John de Pillis is often cited by papers focused on Matrix Theory and Algorithms (23 papers), Advanced Optimization Algorithms Research (11 papers) and Iterative Methods for Nonlinear Equations (5 papers). John de Pillis collaborates with scholars based in United States, United Kingdom and Italy. John de Pillis's co-authors include Wilhelm Niethammer, R. S. Varga, Michael Neumann, Thomas A. Manteuffel, R.C.Y. Chin, J. L. Brenner, A. Hadjidimos and G. Avdelas and has published in prestigious journals such as SIAM Journal on Numerical Analysis, Journal of Mathematical Analysis and Applications and Transactions of the American Mathematical Society.

In The Last Decade

John de Pillis

26 papers receiving 267 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
John de Pillis	220	125	97	77	67	30	361
Xuefeng Duan	246 1.1×	126 1.0×	41 0.4×	45 0.6×	37 0.6×	44	383
F‎. ‎E‎. Levis	227 1.0×	84 0.7×	49 0.5×	29 0.4×	54 0.8×	41	306
Zhongyun Liu	210 1.0×	119 1.0×	57 0.6×	23 0.3×	25 0.4×	47	333
A. Melman	218 1.0×	146 1.2×	39 0.4×	21 0.3×	30 0.4×	52	343
Chun Yuan Deng	245 1.1×	86 0.7×	42 0.4×	23 0.3×	103 1.5×	15	311
Xingping Sheng	306 1.4×	206 1.6×	44 0.5×	34 0.4×	20 0.3×	27	351
Huihui Zhu	328 1.5×	83 0.7×	48 0.5×	34 0.4×	195 2.9×	50	365
James R. Weaver	223 1.0×	87 0.7×	21 0.2×	26 0.3×	60 0.9×	20	356
Vanni Noferini	231 1.1×	129 1.0×	55 0.6×	15 0.2×	37 0.6×	48	359
Shu-Qian Shen	200 0.9×	103 0.8×	79 0.8×	30 0.4×	29 0.4×	30	293

Countries citing papers authored by John de Pillis

Since Specialization

Citations

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

Fields of papers citing papers by John de Pillis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John de Pillis. 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 John de Pillis. The network helps show where John de Pillis may publish in the future.

Co-authorship network of co-authors of John de Pillis

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

All Works

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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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