T. J. Sullivan

75 total papers · 1.2k total citations
24 papers, 664 citations indexed

About

T. J. Sullivan is a scholar working on Artificial Intelligence, Statistics and Probability and Statistics, Probability and Uncertainty. According to data from OpenAlex, T. J. Sullivan has authored 24 papers receiving a total of 664 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 7 papers in Statistics and Probability and 6 papers in Statistics, Probability and Uncertainty. Recurrent topics in T. J. Sullivan's work include Statistical Methods and Inference (7 papers), Probabilistic and Robust Engineering Design (6 papers) and Markov Chains and Monte Carlo Methods (5 papers). T. J. Sullivan is often cited by papers focused on Statistical Methods and Inference (7 papers), Probabilistic and Robust Engineering Design (6 papers) and Markov Chains and Monte Carlo Methods (5 papers). T. J. Sullivan collaborates with scholars based in United Kingdom, Germany and United States. T. J. Sullivan's co-authors include Carl Staelin, Richard Golding, John Wilkes, Samuel Naffziger, T. Grutkowski, Chris J. Oates, V. K. Tewary, An Luo, Ingmar Schuster and John Wilkes and has published in prestigious journals such as Physical Review B, IEEE Journal of Solid-State Circuits and SIAM Journal on Scientific Computing.

In The Last Decade

T. J. Sullivan

24 papers receiving 607 citations

Author Peers

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

Author						Papers	Cites
T. J. Sullivan	149	143	139	103	73	24	664
Mehmet Şahinoglu	76 0.5×	188 1.3×	52 0.4×	132 1.3×	140 1.9×	71	779
Anthony Brockwell	143 1.0×	85 0.6×	32 0.2×	33 0.3×	170 2.3×	37	758
David W. Kammler	127 0.9×	234 1.6×	15 0.1×	154 1.5×	29 0.4×	52	673
Avinash Malik	105 0.7×	42 0.3×	34 0.2×	192 1.9×	55 0.8×	74	718
Graham Horton	101 0.7×	104 0.7×	24 0.2×	81 0.8×	62 0.8×	58	738
Harvey Dubner	55 0.4×	49 0.3×	31 0.2×	24 0.2×	25 0.3×	22	573
Arch W. Naylor	66 0.4×	65 0.5×	29 0.2×	23 0.2×	67 0.9×	21	682
Peter Hellekalek	53 0.4×	40 0.3×	126 0.9×	25 0.2×	183 2.5×	34	750
Amith Singhee	37 0.2×	640 4.5×	125 0.9×	354 3.4×	45 0.6×	38	793
Ludolf Erwin Meester	54 0.4×	64 0.4×	46 0.3×	9 0.1×	82 1.1×	13	639

Countries citing papers authored by T. J. Sullivan

Since Specialization

Citations

This map shows the geographic impact of T. J. Sullivan'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 T. J. Sullivan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. J. Sullivan more than expected).

Fields of papers citing papers by T. J. Sullivan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. J. Sullivan

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