James Tu

26 total papers · 581 total citations
7 papers, 167 citations indexed

About

James Tu is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, James Tu has authored 7 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Automotive Engineering, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in James Tu's work include Autonomous Vehicle Technology and Safety (3 papers), Advanced Neural Network Applications (2 papers) and Layered Double Hydroxides Synthesis and Applications (1 paper). James Tu is often cited by papers focused on Autonomous Vehicle Technology and Safety (3 papers), Advanced Neural Network Applications (2 papers) and Layered Double Hydroxides Synthesis and Applications (1 paper). James Tu collaborates with scholars based in Canada, United States and Australia. James Tu's co-authors include Sergio Casas, Raquel Urtasun, Zhiming Hu, Abbas Sadat, Baochun Li, Sivabalan Manivasagam, Jingkang Wang, Mengye Ren, Kelvin K. L. Wong and Simon Su and has published in prestigious journals such as Neurosurgery, Materials science forum and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In The Last Decade

James Tu

7 papers receiving 159 citations

Author Peers

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

Author						Papers	Cites
James Tu	85	55	36	35	29	7	167
Simon Fürst	77 0.9×	39 0.7×	62 1.7×	39 1.1×	44 1.5×	11	208
Henry Alexander Ignatious	97 1.1×	44 0.8×	47 1.3×	40 1.1×	40 1.4×	12	237
Marcus Nolte	51 0.6×	48 0.9×	23 0.6×	36 1.0×	42 1.4×	19	161
Muhammad Rusyadi Ramli	64 0.8×	29 0.5×	23 0.6×	77 2.2×	34 1.2×	13	237
Jens Oehlerking	59 0.7×	43 0.8×	35 1.0×	19 0.5×	68 2.3×	15	206
Jack Weast	116 1.4×	36 0.7×	54 1.5×	55 1.6×	49 1.7×	11	215
Fengjun Zhou	134 1.6×	53 1.0×	22 0.6×	60 1.7×	68 2.3×	6	275
Rodrigo Queiroz	61 0.7×	88 1.6×	19 0.5×	42 1.2×	20 0.7×	9	189
Daocheng Fu	71 0.8×	54 1.0×	42 1.2×	17 0.5×	73 2.5×	16	238
Daniel J. Fremont	27 0.3×	68 1.2×	15 0.4×	15 0.4×	11 0.4×	10	119

Countries citing papers authored by James Tu

Since Specialization

Citations

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

Fields of papers citing papers by James Tu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Tu

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