Mahsa Ebrahimian

477 total citations · 1 hit paper
7 papers, 248 citations indexed

About

Mahsa Ebrahimian is a scholar working on Information Systems, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, Mahsa Ebrahimian has authored 7 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Information Systems, 3 papers in Management Science and Operations Research and 2 papers in Computer Networks and Communications. Recurrent topics in Mahsa Ebrahimian's work include Recommender Systems and Techniques (3 papers), Advanced Bandit Algorithms Research (3 papers) and Energy Harvesting in Wireless Networks (1 paper). Mahsa Ebrahimian is often cited by papers focused on Recommender Systems and Techniques (3 papers), Advanced Bandit Algorithms Research (3 papers) and Energy Harvesting in Wireless Networks (1 paper). Mahsa Ebrahimian collaborates with scholars based in Canada and Australia. Mahsa Ebrahimian's co-authors include Rasha Kashef, Ahmed Ibrahim, Dina Nawara, Rasha Kashef, Kamal El‐Sankary, E.I. El-Masry and Fatemeh Kazemi and has published in prestigious journals such as Applied Sciences, Urban forestry & urban greening and Symmetry.

In The Last Decade

Mahsa Ebrahimian

7 papers receiving 230 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities

2020 196 citations Mahsa Ebrahimian, Dina Nawara et al. Applied Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mahsa Ebrahimian Canada	5	148	114	40	33	26	7	248
Mala Dutta India	5	135 0.9×	98 0.9×	43 1.1×	34 1.0×	44 1.7×	18	280
Deepjyoti Roy India	4	124 0.8×	97 0.9×	27 0.7×	34 1.0×	41 1.6×	12	256
Dina Nawara Canada	8	186 1.3×	143 1.3×	66 1.6×	40 1.2×	42 1.6×	13	331
Bogdan Walek Czechia	6	181 1.2×	118 1.0×	28 0.7×	37 1.1×	53 2.0×	33	267
Solange Nice Alves-Souza Brazil	7	116 0.8×	141 1.2×	30 0.8×	26 0.8×	28 1.1×	30	266
Sepideh Bazzaz Abkenar Iran	5	93 0.6×	100 0.9×	56 1.4×	35 1.1×	10 0.4×	6	256
Hengliang Luo China	11	215 1.5×	148 1.3×	24 0.6×	28 0.8×	44 1.7×	22	300
Lucas Maystre Switzerland	9	154 1.0×	115 1.0×	24 0.6×	57 1.7×	59 2.3×	15	330
C. Sunitha India	8	104 0.7×	243 2.1×	37 0.9×	59 1.8×	16 0.6×	19	368
Elviawaty Muisa Zamzami Indonesia	9	156 1.1×	134 1.2×	17 0.4×	24 0.7×	48 1.8×	53	360

Countries citing papers authored by Mahsa Ebrahimian

Since Specialization

Citations

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

Fields of papers citing papers by Mahsa Ebrahimian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahsa Ebrahimian

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

All Works

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7 of 7 papers shown

1.

Kazemi, Fatemeh, et al.. (2023). People’s preferences and perceptions toward low-input versus conventional park design approaches using 3D images and interview-based questionnaires. Urban forestry & urban greening. 86. 128040–128040. 5 indexed citations

2.

Ebrahimian, Mahsa, et al.. (2022). Early Detection of Heart Disease Using Advances of Machine Learning for Large-Scale Patient Datasets. 274–280. 2 indexed citations

3.

Ebrahimian, Mahsa & Rasha Kashef. (2021). A CNN-based Hybrid Model and Architecture for Shilling Attack Detection. 12. 1–7. 3 indexed citations

4.

Ebrahimian, Mahsa, et al.. (2020). Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities. Applied Sciences. 10(21). 7748–7748. 196 indexed citations breakdown →

5.

Ebrahimian, Mahsa & Rasha Kashef. (2020). Efficient Detection of Shilling’s Attacks in Collaborative Filtering Recommendation Systems Using Deep Learning Models. 460–464. 11 indexed citations

6.

Ebrahimian, Mahsa & Rasha Kashef. (2020). Detecting Shilling Attacks Using Hybrid Deep Learning Models. Symmetry. 12(11). 1805–1805. 20 indexed citations

7.

Ebrahimian, Mahsa, Kamal El‐Sankary, & E.I. El-Masry. (2010). Enhanced RF to DC CMOS rectifier with capacitor-bootstrapped transistor. 1655–1658. 11 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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