Shima Khoshraftar

546 total citations
9 papers, 258 citations indexed

About

Shima Khoshraftar is a scholar working on Artificial Intelligence, Molecular Biology and Statistical and Nonlinear Physics. According to data from OpenAlex, Shima Khoshraftar has authored 9 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Molecular Biology and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Shima Khoshraftar's work include Advanced Graph Neural Networks (5 papers), Complex Network Analysis Techniques (4 papers) and Graph Theory and Algorithms (2 papers). Shima Khoshraftar is often cited by papers focused on Advanced Graph Neural Networks (5 papers), Complex Network Analysis Techniques (4 papers) and Graph Theory and Algorithms (2 papers). Shima Khoshraftar collaborates with scholars based in Canada, France and Sweden. Shima Khoshraftar's co-authors include Aijun An, Sedigheh Mahdavi, Alan M Moses, Jonas Warringer, Neel Mehta, Dinesh Christendat, Yunchen Gong, Cheuk Chuen Siow, Francisco A. Cubillos and Stacy Hung and has published in prestigious journals such as BMC Genomics, ACM Transactions on Intelligent Systems and Technology and Archives The Journal of the British Records Association.

In The Last Decade

Shima Khoshraftar

7 papers receiving 254 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Shima Khoshraftar Canada	5	113	99	61	43	42	9	258
Felipe Llinares-López Switzerland	11	102 0.9×	174 1.8×	22 0.4×	7 0.2×	36 0.9×	14	352
Sharlee Climer United States	12	52 0.5×	75 0.8×	12 0.2×	8 0.2×	29 0.7×	31	321
Noah M. Daniels United States	12	74 0.7×	240 2.4×	17 0.3×	6 0.1×	8 0.2×	27	383
Saliya Ekanayake United States	9	51 0.5×	61 0.6×	24 0.4×	4 0.1×	33 0.8×	27	247
G. Manjunath India	9	156 1.4×	69 0.7×	52 0.9×	8 0.2×	12 0.3×	31	338
Xuchao Guo China	14	178 1.6×	20 0.2×	10 0.2×	13 0.3×	76 1.8×	37	452
Liliana Ironi Italy	11	122 1.1×	105 1.1×	10 0.2×	8 0.2×	26 0.6×	34	315
Zhanfang Chen China	10	71 0.6×	29 0.3×	20 0.3×	12 0.3×	47 1.1×	27	336
Yifei Shen China	8	87 0.8×	62 0.6×	7 0.1×	6 0.1×	78 1.9×	22	417
Zhengdao Chen United States	8	54 0.5×	565 5.7×	37 0.6×	23 0.5×	117 2.8×	12	714

Countries citing papers authored by Shima Khoshraftar

Since Specialization

Citations

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

Fields of papers citing papers by Shima Khoshraftar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shima Khoshraftar

This figure shows the co-authorship network connecting the top 25 collaborators of Shima Khoshraftar. A scholar is included among the top collaborators of Shima Khoshraftar 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 Shima Khoshraftar. Shima Khoshraftar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Khoshraftar, Shima, et al.. (2025). GraphiT: Efficient Node Classification on Text-Attributed Graphs with Prompt Optimized LLMs. 1824–1829.

2.

Khoshraftar, Shima & Aijun An. (2023). A Survey on Graph Representation Learning Methods. ACM Transactions on Intelligent Systems and Technology. 15(1). 1–55. 79 indexed citations

3.

Khoshraftar, Shima, et al.. (2022). Temporal Graph Representation Learning via Maximal Cliques. 2022 IEEE International Conference on Big Data (Big Data). 4 indexed citations

4.

Khoshraftar, Shima, Sedigheh Mahdavi, & Aijun An. (2021). Centrality-based Interpretability Measures for Graph Embeddings. 1–10. 2 indexed citations

5.

Mahdavi, Sedigheh, Shima Khoshraftar, & Aijun An. (2018). dynnode2vec: Scalable Dynamic Network Embedding. 3762–3765. 62 indexed citations

6.

Gervers, Michael, et al.. (2018). THE DATING OF UNDATED MEDIEVAL CHARTERS. Archives The Journal of the British Records Association. 53(137). 1–33. 1 indexed citations

7.

Khoshraftar, Shima, Stacy Hung, Sadia Khan, et al.. (2013). Sequencing and annotation of the Ophiostoma ulmigenome. BMC Genomics. 14(1). 162–162. 37 indexed citations

8.

Liti, Gianni, Alex N. Nguyen Ba, Martin Blythe, et al.. (2013). High quality de novo sequencing and assembly of the Saccharomyces arboricolus genome. BMC Genomics. 14(1). 69–69. 64 indexed citations

9.

Ilie, Lucian, et al.. (2011). Seeds for effective oligonucleotide design. BMC Genomics. 12(1). 280–280. 9 indexed citations

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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