Mr. Mohammad Hossein Aghahadi | Geochemistry | Best Researcher Award
Mr. Mohammad Hossein Aghahadi | Geochemistry – PhD Student at University of Tehran, Iran
Mohammad Hossein Aghahadi is a prominent figure in the realm of mining engineering, currently advancing his doctoral studies at the School of Mining Engineering, University of Tehran. His academic and research pursuits are deeply rooted in the integration of machine learning methodologies with geochemical data analysis, aiming to revolutionize mineral exploration techniques.
Profile:
Orcid | Scopus
Education:
In September 2023, Aghahadi commenced his PhD journey at the University of Tehran, focusing on mining engineering. This strategic move underscores his dedication to pioneering advancements in geochemical data analysis and mineral exploration.
Research Interests:
Aghahadi’s research is primarily centered on the application of machine learning techniques to geochemical data analysis. His work aims to enhance the accuracy of mineral prospectivity mapping and geochemical anomaly detection, contributing significantly to the efficiency of mineral exploration processes.
Publications:
Throughout his academic career, Aghahadi has contributed to several notable publications:
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“Enhancing regional-scale Pb–Zn prospectivity mapping through data augmentation: Joint application of unsupervised random forests and convolutional neural network” (2025)
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Journal: Earth Science Informatics
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DOI: 10.1007/s12145-025-01843-8
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Citation: This article has been cited by multiple subsequent studies, reflecting its impact on the field.
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“Geochemical anomaly separation based on geology, geostatistics, compositional data and local singularity analyses: A case study from the kuh panj copper deposit, Iran” (2024)
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Journal: Applied Geochemistry
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DOI: 10.1016/j.apgeochem.2024.106135
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Citation: This research has informed various subsequent analyses in geochemical anomaly detection.
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“Spatial Clustering of Primary Geochemical Halos Using Unsupervised Machine Learning in Sari Gunay Gold Deposit, Iran” (2024)
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Journal: Mining, Metallurgy & Exploration
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DOI: 10.1007/s42461-024-01065-4
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Citation: The methodologies presented have been referenced in studies focusing on geochemical clustering techniques.
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Conclusion:
Mohammad Hossein Aghahadi’s scholarly endeavors exemplify a harmonious blend of geological expertise and data science acumen. His publications not only advance the understanding of geochemical processes but also introduce innovative methodologies for data analysis in mineral exploration. His ongoing PhD research holds promise for further contributions to the mining engineering sector, particularly in enhancing the efficiency and precision of geochemical analyses.