Reza Ghezelbash

2.0k total citations
48 papers, 1.4k citations indexed

About

Reza Ghezelbash is a scholar working on Artificial Intelligence, Media Technology and Environmental Engineering. According to data from OpenAlex, Reza Ghezelbash has authored 48 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Artificial Intelligence, 37 papers in Media Technology and 14 papers in Environmental Engineering. Recurrent topics in Reza Ghezelbash's work include Geochemistry and Geologic Mapping (44 papers), Remote-Sensing Image Classification (37 papers) and Soil Geostatistics and Mapping (13 papers). Reza Ghezelbash is often cited by papers focused on Geochemistry and Geologic Mapping (44 papers), Remote-Sensing Image Classification (37 papers) and Soil Geostatistics and Mapping (13 papers). Reza Ghezelbash collaborates with scholars based in Iran, South Africa and Australia. Reza Ghezelbash's co-authors include Abbas Maghsoudi, Mehrdad Daviran, Emmanuel John M. Carranza, Mahsa Hajihosseinlou, Biswajeet Pradhan, Mohammad Parsa, David Cohen, Mohammad Parsa, Hamidreza Ramazi and C. K. Ellis and has published in prestigious journals such as The Science of The Total Environment, Expert Systems with Applications and Computers & Geosciences.

In The Last Decade

Reza Ghezelbash

45 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Reza Ghezelbash Iran	25	1.0k	611	360	355	251	48	1.4k
M. Chica-Rivas Spain	5	575 0.6×	302 0.5×	347 1.0×	409 1.2×	136 0.5×	7	1.5k
Snehamoy Chatterjee United States	26	601 0.6×	301 0.5×	678 1.9×	358 1.0×	158 0.6×	96	1.7k
Maysam Abedi Iran	20	1.0k 1.0×	564 0.9×	409 1.1×	431 1.2×	159 0.6×	82	1.5k
Zhenjie Zhang China	25	1.2k 1.1×	347 0.6×	315 0.9×	253 0.7×	176 0.7×	98	1.7k
Gholam‐Hossain Norouzi Iran	17	709 0.7×	411 0.7×	320 0.9×	313 0.9×	152 0.6×	33	1.1k
Yihui Xiong China	28	2.5k 2.4×	1.3k 2.2×	1.5k 4.2×	594 1.7×	577 2.3×	46	2.8k
Nader Fathianpour Iran	15	254 0.2×	98 0.2×	224 0.6×	206 0.6×	94 0.4×	52	738
I. Kanellopoulos Italy	11	250 0.2×	362 0.6×	57 0.2×	120 0.3×	58 0.2×	30	919
Huimin Wang China	15	116 0.1×	60 0.1×	171 0.5×	125 0.4×	182 0.7×	55	783
Yongyang Xu China	24	248 0.2×	855 1.4×	78 0.2×	752 2.1×	26 0.1×	62	2.0k

Countries citing papers authored by Reza Ghezelbash

Since Specialization

Citations

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

Fields of papers citing papers by Reza Ghezelbash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reza Ghezelbash

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

All Works

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20 of 20 papers shown

Hajihosseinlou, Mahsa, Abbas Maghsoudi, & Reza Ghezelbash. (2025). A semi-supervised learning framework for intelligent mineral prospectivity mapping: Incorporation of the CatBoost and Gaussian mixture model algorithms. Journal of Geochemical Exploration. 274. 107755–107755. 6 indexed citations

Hajihosseinlou, Mahsa, Abbas Maghsoudi, & Reza Ghezelbash. (2025). A semi-supervised approach for mineral prospectivity mapping via weighted positive-unlabeled learning and tree-structured parzen estimator for hyperparameter optimization. Ore Geology Reviews. 185. 106783–106783. 2 indexed citations

Ghezelbash, Reza, et al.. (2025). Evaluation of SOM, DBSCAN, and K-series clustering algorithms for Cu Au anomaly exploration in sample catchment basins: A case study from Hashtjin district, NW Iran. Journal of Geochemical Exploration. 282. 107959–107959.

Ghezelbash, Reza, Mehrdad Daviran, & Abbas Maghsoudi. (2025). Combination of machine learning and fractal approaches for AI-MPM: Identifying low-risk exploration targets associated with porphyry-Cu deposits in the Kerman belt, Iran. Remote Sensing Applications Society and Environment. 38. 101596–101596.

Ramazi, Hamidreza, et al.. (2024). A data-driven VIKOR procedure for predictive modeling of porphyry copper prospectivity in SE Iran. Journal of Geochemical Exploration. 259. 107414–107414. 3 indexed citations

Hajihosseinlou, Mahsa, Abbas Maghsoudi, & Reza Ghezelbash. (2024). Intelligent mapping of geochemical anomalies: Adaptation of DBSCAN and mean-shift clustering approaches. Journal of Geochemical Exploration. 258. 107393–107393. 37 indexed citations

Daviran, Mehrdad, Reza Ghezelbash, Mahsa Hajihosseinlou, & Abbas Maghsoudi. (2024). Uncertainty quantification in genetic algorithm-optimized artificial intelligence-based mineral prospectivity models: automated hyperparameter tuning for support vector machines and random forest. Modeling Earth Systems and Environment. 11(1). 11 indexed citations

Hajihosseinlou, Mahsa, Abbas Maghsoudi, & Reza Ghezelbash. (2024). Geochemical Anomaly Detection and Pattern Recognition: A Combined Study of the Apriori Algorithm, Principal Component Analysis, and Spectral Clustering. Minerals. 14(12). 1202–1202. 8 indexed citations

Iaco, Sandra De, et al.. (2024). Spatial multi-criteria approaches for estimating geogenic radon hazard index. The Science of The Total Environment. 956. 176419–176419. 7 indexed citations

10.

Saremi, M., Abbas Maghsoudi, Mahsa Hajihosseinlou, & Reza Ghezelbash. (2024). A hybrid framework for Detection of Multivariate porphyry Cu Signatures and Anomaly Enhancement: Incorporation of SFA, GMPI, and Grey Wolf Optimization. Geochemistry. 84(4). 126207–126207. 7 indexed citations

11.

Daviran, Mehrdad, Abbas Maghsoudi, & Reza Ghezelbash. (2024). Optimized AI-MPM: Application of PSO for tuning the hyperparameters of SVM and RF algorithms. Computers & Geosciences. 195. 105785–105785. 35 indexed citations

12.

Hajihosseinlou, Mahsa, Abbas Maghsoudi, & Reza Ghezelbash. (2023). Stacking: A novel data-driven ensemble machine learning strategy for prediction and mapping of Pb-Zn prospectivity in Varcheh district, west Iran. Expert Systems with Applications. 237. 121668–121668. 68 indexed citations

13.

Ghezelbash, Reza, et al.. (2023). Developing a spatio-temporal interactions model for car crashes using a novel data-driven AHP-TOPSIS. Applied Geography. 162. 103151–103151. 11 indexed citations

14.

Maghsoudi, Abbas, et al.. (2023). Recognizing Geochemical Anomalies Associated with Mineral Resources Using Singularity Analysis and Random Forest Models in the Torud-Chahshirin Belt, Northeast Iran. Minerals. 13(11). 1399–1399. 13 indexed citations

15.

Hajihosseinlou, Mahsa, Abbas Maghsoudi, & Reza Ghezelbash. (2023). A Novel Scheme for Mapping of MVT-Type Pb–Zn Prospectivity: LightGBM, a Highly Efficient Gradient Boosting Decision Tree Machine Learning Algorithm. Natural Resources Research. 32(6). 2417–2438. 75 indexed citations

16.

Daviran, Mehrdad, et al.. (2023). Hybridizing K-means clustering algorithm with harmony search and artificial bee colony optimizers for intelligence mineral prospectivity mapping. Earth Science Informatics. 16(3). 2143–2165. 22 indexed citations

17.

Maghsoudi, Abbas, et al.. (2023). A comparative study of the XGBoost ensemble learning and multilayer perceptron in mineral prospectivity modeling: a case study of the Torud-Chahshirin belt, NE Iran. Earth Science Informatics. 17(1). 483–499. 20 indexed citations

18.

Daviran, Mehrdad, et al.. (2022). Landslide susceptibility prediction using artificial neural networks, SVMs and random forest: hyperparameters tuning by genetic optimization algorithm. International Journal of Environmental Science and Technology. 20(1). 259–276. 73 indexed citations

19.

Ghezelbash, Reza, Abbas Maghsoudi, & Mehrdad Daviran. (2019). Implementation of Fuzzy-AHP and Fuzzy-GAMMA approaches for discovering the prospectivity areas of Au mineralization in Takhte-Soleyman district. 10(1). 143–162. 7 indexed citations

20.

Ghezelbash, Reza & Abbas Maghsoudi. (2018). Comparison of U-spatial statistics and C–A fractal models for delineating anomaly patterns of porphyry-type Cu geochemical signatures in the Varzaghan district, NW Iran. Comptes Rendus Géoscience. 350(4). 180–191. 47 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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