Morteza Karimzadeh

735 total citations
28 papers, 357 citations indexed

About

Morteza Karimzadeh is a scholar working on Computer Vision and Pattern Recognition, Geography, Planning and Development and Artificial Intelligence. According to data from OpenAlex, Morteza Karimzadeh has authored 28 papers receiving a total of 357 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 8 papers in Geography, Planning and Development and 7 papers in Artificial Intelligence. Recurrent topics in Morteza Karimzadeh's work include Geographic Information Systems Studies (8 papers), Data Visualization and Analytics (8 papers) and COVID-19 epidemiological studies (5 papers). Morteza Karimzadeh is often cited by papers focused on Geographic Information Systems Studies (8 papers), Data Visualization and Analytics (8 papers) and COVID-19 epidemiological studies (5 papers). Morteza Karimzadeh collaborates with scholars based in United States, United Kingdom and Germany. Morteza Karimzadeh's co-authors include Alan M. MacEachren, Jan Oliver Wallgrün, Scott Pezanowski, Behzad Vahedi, David S. Ebert, Yi‐Shan Lin, Dan Goldwasser, Rafael Pires de Lima, Frank Hardisty and J. L. Zhao and has published in prestigious journals such as Nature Communications, IEEE Transactions on Geoscience and Remote Sensing and International Journal of Remote Sensing.

In The Last Decade

Morteza Karimzadeh

24 papers receiving 345 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Morteza Karimzadeh United States 10 137 134 63 54 50 28 357
Clemens Havas Austria 10 92 0.7× 90 0.7× 19 0.3× 104 1.9× 70 1.4× 15 441
Víctor Soto United States 10 147 1.1× 44 0.3× 58 0.9× 266 4.9× 65 1.3× 23 474
Abish Malik United States 12 103 0.8× 47 0.4× 77 1.2× 47 0.9× 40 0.8× 30 430
Franz‐Benjamin Mocnik Germany 11 26 0.2× 154 1.1× 74 1.2× 73 1.4× 52 1.0× 29 303
Sathya Prasad United States 6 54 0.4× 117 0.9× 76 1.2× 179 3.3× 30 0.6× 8 343
Stefano Modafferi Italy 8 130 0.9× 66 0.5× 23 0.4× 58 1.1× 45 0.9× 22 410
Laura Spinsanti Italy 9 56 0.4× 211 1.6× 137 2.2× 199 3.7× 61 1.2× 15 423
Shamanth Kumar United States 10 234 1.7× 47 0.4× 40 0.6× 63 1.2× 43 0.9× 13 592
Caglar Koylu United States 11 55 0.4× 42 0.3× 34 0.5× 79 1.5× 17 0.3× 22 296
Stephen Rudolph United States 6 68 0.5× 38 0.3× 59 0.9× 41 0.8× 69 1.4× 8 295

Countries citing papers authored by Morteza Karimzadeh

Since Specialization
Citations

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

Fields of papers citing papers by Morteza Karimzadeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Morteza Karimzadeh

This figure shows the co-authorship network connecting the top 25 collaborators of Morteza Karimzadeh. A scholar is included among the top collaborators of Morteza Karimzadeh 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 Morteza Karimzadeh. Morteza Karimzadeh 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.
Ngô, Thoại D., et al.. (2025). Integrating spatiotemporal features in LSTM for spatially informed COVID-19 hospitalization forecasting. International Journal of Geographical Information Systems. 1–38.
2.
Lima, Rafael Pires de, et al.. (2025). Enhancing and Interpreting Deep Learning for Sea Ice Charting using the AutoICE Benchmark. Remote Sensing Applications Society and Environment. 38. 101538–101538. 1 indexed citations
3.
Karimzadeh, Morteza, et al.. (2025). Microfluidic droplet detection using synthetic data generated by a Generative Adversarial Network. Engineering Applications of Artificial Intelligence. 156. 111032–111032.
4.
Messina, Jane P., et al.. (2025). GeoDEN: A Visual Exploration Tool for Analyzing the Geographic Spread of Dengue Serotypes. Computer Graphics Forum. 44(6).
5.
Crooks, James, et al.. (2025). High-Resolution Estimation of Daily PM2.5 Levels in the Contiguous US Using Bi-LSTM with Attention. Remote Sensing. 17(1). 126–126. 3 indexed citations
6.
Pezzı, Laura, Daniel G. Olson, Jane P. Messina, et al.. (2024). Assessing vulnerability for future Zika virus outbreaks using seroprevalence data and environmental suitability maps. PLoS neglected tropical diseases. 18(3). e0012017–e0012017. 2 indexed citations
7.
8.
Lima, Rafael Pires de, et al.. (2023). Increasing the Spatial Coverage of Atmospheric Aerosol Depth Measurements using Random Forest and Mean Filters. PubMed. 2023. 3928–3931. 1 indexed citations
9.
Karimzadeh, Morteza, et al.. (2023). Alternatives to Contour Visualizations for Power Systems Data. 11–15. 2 indexed citations
10.
Lima, Rafael Pires de, Behzad Vahedi, Nick Hughes, et al.. (2023). Enhancing sea ice segmentation in Sentinel-1 images with atrous convolutions. International Journal of Remote Sensing. 44(17). 5344–5374. 7 indexed citations
11.
Lima, Rafael Pires de, Behzad Vahedi, & Morteza Karimzadeh. (2023). Comparison of Cross-Entropy, Dice, and Focal Loss for Sea Ice Type Segmentation. arXiv (Cornell University). 145–148. 1 indexed citations
12.
Vahedi, Behzad, et al.. (2022). A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA. International Journal of Data Science and Analytics. 15(3). 247–266. 25 indexed citations
13.
Vahedi, Behzad, et al.. (2021). Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions. Nature Communications. 12(1). 6440–6440. 24 indexed citations
14.
Karimzadeh, Morteza, Scott Pezanowski, Alan M. MacEachren, & Jan Oliver Wallgrün. (2019). GeoTxt: A scalable geoparsing system for unstructured text geolocation. Transactions in GIS. 23(1). 118–136. 71 indexed citations
15.
Lin, Yi‐Shan, et al.. (2019). Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness. IEEE Transactions on Visualization and Computer Graphics. 26(1). 1–1. 38 indexed citations
16.
Karimzadeh, Morteza, et al.. (2019). VASSL: A Visual Analytics Toolkit for Social Spambot Labeling. IEEE Transactions on Visualization and Computer Graphics. 26(1). 874–883. 16 indexed citations
17.
Zhao, J. L., et al.. (2019). MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies. IEEE Transactions on Visualization and Computer Graphics. 26(1). 1–1. 5 indexed citations
18.
Wallgrün, Jan Oliver, Morteza Karimzadeh, Alan M. MacEachren, & Scott Pezanowski. (2017). GeoCorpora: building a corpus to test and train microblog geoparsers. International Journal of Geographical Information Systems. 32(1). 1–29. 67 indexed citations
19.
Wallgrün, Jan Oliver, Alexander Klippel, & Morteza Karimzadeh. (2015). Towards contextualized models of spatial relations. Data Archiving and Networked Services (DANS). 1–2. 3 indexed citations
20.
Karimzadeh, Morteza, Wenyi Huang, Siddhartha Banerjee, et al.. (2013). GeoTxt. 72–73. 34 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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