Andrew Guillory

23 total papers · 539 total citations
11 papers, 295 citations indexed

About

Andrew Guillory is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Andrew Guillory has authored 11 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 3 papers in Computer Networks and Communications. Recurrent topics in Andrew Guillory's work include Machine Learning and Algorithms (6 papers), Complexity and Algorithms in Graphs (4 papers) and Advanced Bandit Algorithms Research (2 papers). Andrew Guillory is often cited by papers focused on Machine Learning and Algorithms (6 papers), Complexity and Algorithms in Graphs (4 papers) and Advanced Bandit Algorithms Research (2 papers). Andrew Guillory collaborates with scholars based in United States and United Kingdom. Andrew Guillory's co-authors include Jeff Bilmes, T. Scott Saponas, Dan Morris, Ajit Singh, Tucker Balch, Charles L. Isbell, Frank Dellaert, Adam S. Feldman, Zia U. Khan and Andrew N. Stein and has published in prestigious journals such as Proceedings of the IEEE, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Andrew Guillory

10 papers receiving 283 citations

Author Peers

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

Author						Papers	Cites
Andrew Guillory	128	99	59	44	42	11	295
Alberto Alvarez-Alvarez	141 1.1×	99 1.0×	31 0.5×	69 1.6×	43 1.0×	13	301
Christian Osendorfer	153 1.2×	70 0.7×	13 0.2×	46 1.0×	38 0.9×	15	339
Vassilis Vassiliades	229 1.8×	44 0.4×	56 0.9×	38 0.9×	51 1.2×	22	348
Lucija Brezočnik	229 1.8×	56 0.6×	40 0.7×	36 0.8×	47 1.1×	9	356
Víctor Uc-Cetina	92 0.7×	115 1.2×	26 0.4×	23 0.5×	30 0.7×	18	323
Michael D. Wagner	158 1.2×	99 1.0×	97 1.6×	28 0.6×	17 0.4×	11	356
Yi-Ting Chiang	94 0.7×	145 1.5×	69 1.2×	9 0.2×	26 0.6×	17	268
Dmitri Asonov	178 1.4×	78 0.8×	42 0.7×	9 0.2×	16 0.4×	10	338
Ajay Mandlekar	168 1.3×	87 0.9×	15 0.3×	35 0.8×	12 0.3×	14	305
Jo Devriendt	180 1.4×	65 0.7×	46 0.8×	5 0.1×	26 0.6×	10	299

Countries citing papers authored by Andrew Guillory

Since Specialization

Citations

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

Fields of papers citing papers by Andrew Guillory

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Guillory

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Guillory. A scholar is included among the top collaborators of Andrew Guillory 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 Andrew Guillory. Andrew Guillory 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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