I. R. Goodman

110 total papers · 1.4k total citations
47 papers, 794 citations indexed

About

I. R. Goodman is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computational Theory and Mathematics. According to data from OpenAlex, I. R. Goodman has authored 47 papers receiving a total of 794 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 16 papers in Management Science and Operations Research and 12 papers in Computational Theory and Mathematics. Recurrent topics in I. R. Goodman's work include Bayesian Modeling and Causal Inference (24 papers), Logic, Reasoning, and Knowledge (18 papers) and Multi-Criteria Decision Making (14 papers). I. R. Goodman is often cited by papers focused on Bayesian Modeling and Causal Inference (24 papers), Logic, Reasoning, and Knowledge (18 papers) and Multi-Criteria Decision Making (14 papers). I. R. Goodman collaborates with scholars based in United States and Mexico. I. R. Goodman's co-authors include Hung T. Nguyen, Ronald Mahler, Hung T. Nguyen, Samuel Kotz, Donald Bamber, Gerald S. Rogers, Владик Крейнович, Jesús Ibáñez, Theodore V. Galambos and Michael P. Windham and has published in prestigious journals such as Information Sciences, Fuzzy Sets and Systems and Journal of Mathematical Analysis and Applications.

In The Last Decade

I. R. Goodman

41 papers receiving 715 citations

Author Peers

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

Author						Papers	Cites
I. R. Goodman	606	202	158	130	121	47	794
Alessio Benavoli	489 0.8×	76 0.4×	156 1.0×	65 0.5×	80 0.7×	72	751
Arnaud Martin	484 0.8×	188 0.9×	51 0.3×	130 1.0×	56 0.5×	52	894
Tim Zajic	283 0.5×	198 1.0×	230 1.5×	26 0.2×	144 1.2×	32	715
Stefano Zambelli	479 0.8×	132 0.7×	82 0.5×	58 0.4×	66 0.5×	30	886
Tim van Erven	450 0.7×	111 0.5×	104 0.7×	48 0.4×	125 1.0×	17	931
Frederick J. Beutler	161 0.3×	97 0.5×	209 1.3×	103 0.8×	73 0.6×	47	949
Vladislav B. Tadić	485 0.8×	66 0.3×	108 0.7×	54 0.4×	110 0.9×	43	783
Khaled Mellouli	512 0.8×	252 1.2×	59 0.4×	168 1.3×	55 0.5×	41	723
Galina L. Rogova	577 1.0×	163 0.8×	105 0.7×	41 0.3×	21 0.2×	44	915
Javier Yáñez	200 0.3×	242 1.2×	55 0.3×	180 1.4×	61 0.5×	52	713

Countries citing papers authored by I. R. Goodman

Since Specialization

Citations

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

Fields of papers citing papers by I. R. Goodman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by I. R. Goodman. 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 I. R. Goodman. The network helps show where I. R. Goodman may publish in the future.

Co-authorship network of co-authors of I. R. Goodman

This figure shows the co-authorship network connecting the top 25 collaborators of I. R. Goodman. A scholar is included among the top collaborators of I. R. Goodman 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 I. R. Goodman. I. R. Goodman 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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