Tara Safavi

47 total papers · 726 total citations
20 papers, 314 citations indexed

About

Tara Safavi is a scholar working on Artificial Intelligence, Management Science and Operations Research and Statistical and Nonlinear Physics. According to data from OpenAlex, Tara Safavi has authored 20 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 6 papers in Management Science and Operations Research and 5 papers in Statistical and Nonlinear Physics. Recurrent topics in Tara Safavi's work include Topic Modeling (10 papers), Advanced Graph Neural Networks (7 papers) and Natural Language Processing Techniques (6 papers). Tara Safavi is often cited by papers focused on Topic Modeling (10 papers), Advanced Graph Neural Networks (7 papers) and Natural Language Processing Techniques (6 papers). Tara Safavi collaborates with scholars based in United States, United Kingdom and Switzerland. Tara Safavi's co-authors include Danai Koutra, Mark Heimann, Davide Mottin, Emmanuel Müller, Chandra Sripada, Neil Shah, Jing Zhu, Wei‐Chen Lee, Di Jin and Paul N. Bennett and has published in prestigious journals such as ACM Computing Surveys, Knowledge and Information Systems and Social Network Analysis and Mining.

In The Last Decade

Tara Safavi

19 papers receiving 311 citations

Author Peers

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

Author						Papers	Cites
Tara Safavi	224	88	84	53	48	20	314
Yozen Liu	253 1.1×	61 0.7×	72 0.9×	42 0.8×	89 1.9×	20	350
Kangfei Zhao	190 0.8×	42 0.5×	91 1.1×	53 1.0×	35 0.7×	26	252
Thanh Trung Huynh	229 1.0×	79 0.9×	70 0.8×	24 0.5×	89 1.9×	33	340
Chi Thang Duong	170 0.8×	57 0.6×	44 0.5×	22 0.4×	74 1.5×	15	247
Xing Li	166 0.7×	124 1.4×	31 0.4×	87 1.6×	84 1.8×	29	332
Matthew J. Rattigan	138 0.6×	161 1.8×	34 0.4×	81 1.5×	49 1.0×	15	261
Weiren Yu	153 0.7×	103 1.2×	79 0.9×	92 1.7×	79 1.6×	18	319
Joseph J. Pfeiffer	116 0.5×	81 0.9×	41 0.5×	31 0.6×	37 0.8×	28	239
Cheng Ji	245 1.1×	39 0.4×	51 0.6×	30 0.6×	49 1.0×	16	360
Paolo Rosso	179 0.8×	42 0.5×	44 0.5×	23 0.4×	85 1.8×	16	289

Countries citing papers authored by Tara Safavi

Since Specialization

Citations

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

Fields of papers citing papers by Tara Safavi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tara Safavi

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