Mahsa Shakeri

571 total citations
20 papers, 365 citations indexed

About

Mahsa Shakeri is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Mahsa Shakeri has authored 20 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Computer Networks and Communications and 3 papers in Artificial Intelligence. Recurrent topics in Mahsa Shakeri's work include Medical Image Segmentation Techniques (5 papers), Software System Performance and Reliability (3 papers) and Image Retrieval and Classification Techniques (3 papers). Mahsa Shakeri is often cited by papers focused on Medical Image Segmentation Techniques (5 papers), Software System Performance and Reliability (3 papers) and Image Retrieval and Classification Techniques (3 papers). Mahsa Shakeri collaborates with scholars based in Iran, Canada and Switzerland. Mahsa Shakeri's co-authors include Samuel Kadoury, Lisa Di Jorio, Michal Drozdzal, An Tang, Chris Pal, Yoshua Bengio, Adriana Romero, Eugene Vorontsov, Gabriel Chartrand and Sarah Lippé and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Medical Image Analysis.

In The Last Decade

Mahsa Shakeri

19 papers receiving 361 citations

Author Peers

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

Author Last Decade Papers Cites
Mahsa Shakeri 164 134 80 68 65 20 365
Zhuoyuan Li 89 0.5× 121 0.9× 101 1.3× 54 0.8× 34 0.5× 12 301
Alexander Hubert 186 1.1× 145 1.1× 93 1.2× 136 2.0× 37 0.6× 8 380
Nagesh K. Subbanna 219 1.3× 119 0.9× 87 1.1× 139 2.0× 39 0.6× 17 449
Fernando Pérez‐García 107 0.7× 226 1.7× 141 1.8× 41 0.6× 63 1.0× 17 503
April Khademi 173 1.1× 232 1.7× 134 1.7× 99 1.5× 35 0.5× 48 525
Bibo Shi 75 0.5× 159 1.2× 151 1.9× 58 0.9× 29 0.4× 25 375
Ahsan Bin Tufail 84 0.5× 132 1.0× 162 2.0× 146 2.1× 29 0.4× 15 378
Eloy Roura 297 1.8× 208 1.6× 101 1.3× 226 3.3× 73 1.1× 18 666
Pantelis Georgiadis 117 0.7× 152 1.1× 80 1.0× 111 1.6× 38 0.6× 22 386
Jacob C. Reinhold 105 0.6× 210 1.6× 86 1.1× 46 0.7× 62 1.0× 7 393

Countries citing papers authored by Mahsa Shakeri

Since Specialization
Citations

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

Fields of papers citing papers by Mahsa Shakeri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mahsa Shakeri

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

All Works

20 of 20 papers shown
1.
Fernandes, Ajoy Savio, Kiran Somasundaram, Mahsa Shakeri, et al.. (2025). Enabling Eye Tracking for Crowd-Sourced Data Collection With Project Aria. IEEE Access. 13. 114736–114745. 1 indexed citations
2.
Shakeri, Mahsa, et al.. (2024). A Comprehensive Evaluation of Radiomic Features in Normal Brain Magnetic Resonance Imaging: Investigating Robustness and Region Variations. Journal of Medical Physics. 49(4). 608–622. 1 indexed citations
3.
Toossi, Mohammad Taghi Bahreyni, et al.. (2022). The role of microRNA-induced apoptosis in diverse radioresistant cancers. Cellular Signalling. 104. 110580–110580. 16 indexed citations
4.
Aloise, Daniel, et al.. (2021). A Framework for Detecting System Performance Anomalies Using Tracing Data Analysis. Entropy. 23(8). 1011–1011. 9 indexed citations
5.
Shakeri, Mahsa, et al.. (2021). Correlation between Base Transceiver Station and the Quality of Sleep and Life of Nearby Residents. SHILAP Revista de lepidopterología. 18(1). 10–14.
6.
Shakeri, Mahsa, et al.. (2021). Host-Based Virtual Machine Workload Characterization Using Hypervisor Trace Mining. PolyPublie (École Polytechnique de Montréal). 6(1). 1–25. 3 indexed citations
7.
8.
Shakeri, Mahsa, et al.. (2019). Cytogenetic effects of radiation and genetic polymorphisms of the XRCC1 and XRCC3 repair genes in industrial radiographers. Radiation and Environmental Biophysics. 58(2). 247–255. 6 indexed citations
9.
Shakeri, Mahsa, et al.. (2019). System performance anomaly detection using tracing data analysis. PolyPublie (École Polytechnique de Montréal). 169–173. 7 indexed citations
10.
Shakeri, Mahsa, et al.. (2018). Inter-vertebral disk modelling from pairs of segmented vertebral models using trainable pre-processing networks. PolyPublie (École Polytechnique de Montréal). 1122–1125. 3 indexed citations
11.
Drozdzal, Michal, Gabriel Chartrand, Eugene Vorontsov, et al.. (2017). Learning normalized inputs for iterative estimation in medical image segmentation. Medical Image Analysis. 44. 1–13. 181 indexed citations
12.
Shakeri, Mahsa, Alexandre Datta, Laurent Létourneau‐Guillon, et al.. (2017). Sub-cortical brain morphometry and its relationship with cognition in rolandic epilepsy. Epilepsy Research. 138. 39–45. 18 indexed citations
13.
Shakeri, Mahsa, et al.. (2017). Sub-cortical shape morphology and voxel-based features for Alzheimer's disease classification. PolyPublie (École Polytechnique de Montréal). 991–994. 11 indexed citations
14.
Zakeri, Farideh, et al.. (2016). PHYSICIANS’ KNOWLEDGE ABOUT RADIATION DOSE AND POSSIBLE RISKS OF COMMON MEDICAL TESTS: A SURVEY IN IRAN. Radiation Protection Dosimetry. 172(1-3). 311–316. 7 indexed citations
15.
Shakeri, Mahsa, Hervé Lombaert, Alexandre Datta, et al.. (2016). Statistical shape analysis of subcortical structures using spectral matching. Computerized Medical Imaging and Graphics. 52. 58–71. 8 indexed citations
16.
Shakeri, Mahsa, et al.. (2016). A cytogenetic biomonitoring of industrial radiographers occupationally exposed to low levels of ionizing radiation by using cbmn assay. Radiation Protection Dosimetry. 175(2). 246–251. 8 indexed citations
17.
Shakeri, Mahsa, Stavros Tsogkas, Enzo Ferrante, et al.. (2016). Sub-cortical brain structure segmentation using F-CNN'S. arXiv (Cornell University). 69 indexed citations
18.
Shakeri, Mahsa, Hervé Lombaert, Sarah Lippé, & Samuel Kadoury. (2014). Groupwise shape analysis of the hippocampus using spectral matching. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9034. 90340W–90340W. 3 indexed citations
19.
Shakeri, Mahsa & Mansour Jamzad. (2013). A robust zero-watermarking scheme using Canny edge detector. International Journal of Electronic Security and Digital Forensics. 5(1). 25–25. 2 indexed citations
20.
Shakeri, Mahsa & Mansour Jamzad. (2011). A Robust Copyright Protection Scheme Based on Discrete Cosine Transform and Image Normalization. 1–6. 4 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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