Michael J. McCourt

48 total papers · 903 total citations
36 papers, 610 citations indexed

About

Michael J. McCourt is a scholar working on Control and Systems Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Michael J. McCourt has authored 36 papers receiving a total of 610 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Control and Systems Engineering, 15 papers in Computer Networks and Communications and 6 papers in Artificial Intelligence. Recurrent topics in Michael J. McCourt's work include Control and Stability of Dynamical Systems (15 papers), Stability and Control of Uncertain Systems (10 papers) and Petri Nets in System Modeling (6 papers). Michael J. McCourt is often cited by papers focused on Control and Stability of Dynamical Systems (15 papers), Stability and Control of Uncertain Systems (10 papers) and Petri Nets in System Modeling (6 papers). Michael J. McCourt collaborates with scholars based in United States and Italy. Michael J. McCourt's co-authors include Panos J. Antsaklis, Gregory E. Fasshauer, Vijay Gupta, Meng Xia, Nicholas Kottenstette, Po Wu, Feng Zhu, J. Willard Curtis, Ryan M. Robinson and William D. Nothwang and has published in prestigious journals such as IEEE Transactions on Automatic Control, Automatica and Optics Express.

In The Last Decade

Michael J. McCourt

34 papers receiving 586 citations

Author Peers

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

Author						Papers	Cites
Michael J. McCourt	307	120	108	94	93	36	610
Daisuke Tsubakino	378 1.2×	28 0.2×	127 1.2×	104 1.1×	50 0.5×	64	600
Shumon Koga	404 1.3×	24 0.2×	80 0.7×	72 0.8×	59 0.6×	45	553
Zhiming Chen	198 0.6×	50 0.4×	47 0.4×	87 0.9×	86 0.9×	64	562
Jing Li	88 0.3×	95 0.8×	47 0.4×	36 0.4×	33 0.4×	78	547
В.М. Матросов	338 1.1×	115 1.0×	56 0.5×	14 0.1×	29 0.3×	22	616
X. Wang	81 0.3×	261 2.2×	104 1.0×	43 0.5×	59 0.6×	19	604
A. A. Galal	186 0.6×	116 1.0×	40 0.4×	84 0.9×	57 0.6×	41	629
Gerald Moore	78 0.3×	67 0.6×	63 0.6×	171 1.8×	57 0.6×	24	616
Cheng Wang	54 0.2×	88 0.7×	186 1.7×	171 1.8×	87 0.9×	55	649
Juraj Valsa	345 1.1×	31 0.3×	57 0.5×	19 0.2×	317 3.4×	20	620

Countries citing papers authored by Michael J. McCourt

Since Specialization

Citations

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

Fields of papers citing papers by Michael J. McCourt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael J. McCourt. 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 Michael J. McCourt. The network helps show where Michael J. McCourt may publish in the future.

Co-authorship network of co-authors of Michael J. McCourt

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. McCourt. A scholar is included among the top collaborators of Michael J. McCourt 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 Michael J. McCourt. Michael J. McCourt 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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