Mehran Javanmardi

1.3k total citations
9 papers, 379 citations indexed

About

Mehran Javanmardi is a scholar working on Computer Vision and Pattern Recognition, Transportation and Health. According to data from OpenAlex, Mehran Javanmardi has authored 9 papers receiving a total of 379 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Transportation and 3 papers in Health. Recurrent topics in Mehran Javanmardi's work include Urban Transport and Accessibility (4 papers), Health disparities and outcomes (3 papers) and COVID-19 epidemiological studies (2 papers). Mehran Javanmardi is often cited by papers focused on Urban Transport and Accessibility (4 papers), Health disparities and outcomes (3 papers) and COVID-19 epidemiological studies (2 papers). Mehran Javanmardi collaborates with scholars based in United States and Türkiye. Mehran Javanmardi's co-authors include Tolga Taşdizen, Mehdi S. M. Sajjadi, Pallavi Dwivedi, Quynh C. Nguyen, Jessica M. Keralis, Kimberly D. Brunisholz, Dina Huang, Yuru Huang, Abhinav Kumar and Jonathan Jay and has published in prestigious journals such as IEEE Access, International Journal of Environmental Research and Public Health and BMC Public Health.

In The Last Decade

Mehran Javanmardi

9 papers receiving 375 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mehran Javanmardi United States	8	144	125	85	69	62	9	379
Dexuan Sha United States	11	59 0.4×	38 0.3×	32 0.4×	44 0.6×	99 1.6×	24	368
Yun Han China	10	89 0.6×	145 1.2×	56 0.7×	109 1.6×	62 1.0×	21	362
Youngok Kang South Korea	10	26 0.2×	32 0.3×	29 0.3×	99 1.4×	59 1.0×	60	354
Mohammad Anisur Rahaman Bangladesh	8	45 0.3×	55 0.4×	15 0.2×	5 0.1×	15 0.2×	25	370
Nima Nikzad United States	10	29 0.2×	25 0.2×	74 0.9×	26 0.4×	21 0.3×	18	314
Ke Hu China	11	67 0.5×	297 2.4×	9 0.1×	9 0.1×	40 0.6×	35	558
Evaggelia Tsiligianni Belgium	9	47 0.3×	90 0.7×	141 1.7×	28 0.4×	39 0.6×	20	381
Achilleas Psyllidis Netherlands	10	23 0.2×	22 0.2×	54 0.6×	131 1.9×	59 1.0×	27	267
Sangwon Chae South Korea	3	73 0.5×	11 0.1×	70 0.8×	3 0.0×	19 0.3×	7	322

Countries citing papers authored by Mehran Javanmardi

Since Specialization

Citations

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

Fields of papers citing papers by Mehran Javanmardi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mehran Javanmardi

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

All Works

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9 of 9 papers shown

Nguyen, Quynh C., Yuru Huang, Abhinav Kumar, et al.. (2020). Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases. International Journal of Environmental Research and Public Health. 17(17). 6359–6359. 72 indexed citations

Keralis, Jessica M., Mehran Javanmardi, Pallavi Dwivedi, et al.. (2020). Health and the built environment in United States cities: measuring associations using Google Street View-derived indicators of the built environment. BMC Public Health. 20(1). 215–215. 62 indexed citations

Yu, Weijun, Jessica M. Keralis, Pallavi Dwivedi, et al.. (2020). Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States. International Journal of Environmental Research and Public Health. 17(10). 3659–3659. 21 indexed citations

Nguyen, Quynh C., Jessica M. Keralis, Pallavi Dwivedi, et al.. (2020). Leveraging 31 Million Google Street View Images to Characterize Built Environments and Examine County Health Outcomes. Public Health Reports. 136(2). 201–211. 23 indexed citations

Javanmardi, Mehran, Dina Huang, Pallavi Dwivedi, et al.. (2019). Analyzing Associations Between Chronic Disease Prevalence and Neighborhood Quality Through Google Street View Images. IEEE Access. 8. 6407–6416. 8 indexed citations

Taşdizen, Tolga, et al.. (2018). Improving the robustness of convolutional networks to appearance variability in biomedical images. 549–553. 11 indexed citations

Javanmardi, Mehran & Tolga Taşdizen. (2018). Domain adaptation for biomedical image segmentation using adversarial training. 554–558. 64 indexed citations

Javanmardi, Mehran, et al.. (2018). Image Segmentation by Deep Learning of Disjunctive Normal Shape Model Shape Representation. 2. 488–4887. 1 indexed citations

Sajjadi, Mehdi S. M., Mehran Javanmardi, & Tolga Taşdizen. (2016). Regularization with stochastic transformations and perturbations for deep semi-supervised learning. Neural Information Processing Systems. 29. 1171–1179. 117 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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