Dr. Jabar Habashi | Hyperspectral Data Processing | Best Researcher Award
Student at University of Kentucky, Iran
Mr. Jabar Habashi is a dedicated researcher specializing in remote sensing, mineral exploration, and geospatial data science. With a strong academic background and technical expertise, he has contributed to the advancement of hyperspectral image analysis, AI-driven geological mapping, and environmental impact assessment. His work bridges the fields of Earth sciences and data science, focusing on developing predictive models for resource estimation and sustainable land use. Jabar has co-authored over 12 publications in reputed international journals such as ISPRS Journal of Photogrammetry and Remote Sensing and Remote Sensing (MDPI), and presented at leading conferences. He has also served as a reviewer for peer-reviewed journals, demonstrating engagement with the scientific community. Currently working as a Data Scientist at Scan Miner Solutions, Jabar combines practical industry insight with strong research acumen. His interdisciplinary approach and commitment to impactful science make him a promising figure in global geoscience and Earth observation research.
Professional Profile
Education🎓
Jabar Habashi holds a Master of Science in Mining Exploration Engineering from Sahand University of Technology, Iran, completed in 2023. His MSc thesis focused on multispectral data classification using Hyperion satellite data, highlighting the role of remote sensing in mineral exploration. He previously earned a Bachelor of Science in Mineral Engineering from Malayer University in 2019, where his undergraduate research involved processing and analyzing magnetometric data from the Nadushan region in Yazd, Iran. Throughout his academic journey, Jabar was recognized for his academic excellence, earning full scholarships and achieving high ranks in national entrance examinations. His education provided a strong foundation in mining and geological sciences, with a focus on satellite data processing and geospatial analysis. He also gained valuable teaching experience as a teaching assistant in various laboratories, including mineralogy, petrology, and cartography, which reflects his active engagement with both theoretical and hands-on aspects of Earth sciences.
Professional Experience📝
Jabar Habashi is currently working as a Data Scientist at Scan Miner Solutions (since July 2024), where he applies advanced data analytics and remote sensing techniques to solve real-world challenges in the mining and exploration industry. His previous hands-on experience includes internships at the Department of Industry, Mining, and Trade of Sonqor County, and Gelali Iron Mine in Qorveh, Iran, where he gained insights into mining operations and data interpretation. During his academic years, he held several teaching assistant positions at Malayer University, supporting laboratory sessions in descriptive mineralogy, optical mineralogy, petrology, and cartography. These roles not only strengthened his technical and instructional skills but also laid a foundation for future academic contributions. His combination of fieldwork, laboratory training, and data-driven industry experience allows him to connect theoretical research with practical applications. This balanced background equips Jabar with the multidisciplinary insight essential for innovation in geoscience and mining technologies.
Research Interest🔎
Jabar Habashi’s research interests span a broad array of topics within remote sensing, mineral exploration, and environmental geoscience. He is particularly focused on hyperspectral image analysis, multisource data fusion, and AI-driven geological mapping. His work aims to automate mineral target recognition using deep learning, optimize alteration mineral detection, and advance predictive modeling for resource estimation. He is also passionate about hydrologic modeling, LiDAR data processing, climate change analysis, and geohazard assessment, reflecting a strong commitment to sustainable Earth system science. In recent studies, he has explored Antarctic terrains using PRISMA hyperspectral data and contributed to mapping projects in semi-arid and mountainous regions. His interest in mine closure and post-mining land use demonstrates a forward-thinking approach to environmental reclamation and sustainable mining practices. By integrating satellite data, field observations, and AI, Jabar aims to develop tools that enhance decision-making in exploration, environmental monitoring, and climate-sensitive resource management.
Award and Honor🏆
Jabar Habashi has received multiple awards and honors in recognition of his academic excellence and research capabilities. He earned a national rank that secured him admission to Malayer University with a full undergraduate scholarship in the mathematics branch. Later, he achieved a top national ranking in the MSc entrance exam for Mining Exploration Engineering, which granted him a full scholarship at Sahand University of Technology. These distinctions reflect his strong academic caliber and dedication to scholarly achievement. In addition to his academic honors, Jabar has contributed to the scientific community by reviewing manuscripts for respected journals such as Remote Sensing Applications: Society and Environment, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), and Earth Science Informatics. These contributions highlight his growing reputation in the fields of Earth observation and geospatial research. His ongoing commitment to excellence and collaboration makes him a distinguished researcher in his discipline.
Research Skill🔬
Jabar Habashi possesses a wide range of technical and analytical research skills essential for modern geoscientific inquiry. He is proficient in ENVI, ArcGIS Pro, Surfer, MATLAB, and Geosoft Oasis Montaj, with specialization in magnetometry and remote sensing software. He has advanced command of Python programming, particularly for image classification, data preprocessing, and deep learning applications. Jabar’s skill set extends to satellite image fusion, LiDAR and PALSAR data processing, and the integration of field and geospatial datasets for exploration and environmental modeling. He has experience in multispectral and hyperspectral classification, geohazard analysis, and mine site monitoring, showcasing his versatility in both theoretical and applied research. Additionally, he holds multiple certifications in GIS, remote sensing, and Python from Coursera. His analytical capabilities, combined with a deep understanding of geological systems and AI integration, enable him to address complex challenges in mineral exploration and Earth system science with precision and innovation.
Conclusion💡
Mr. Jabar Habashi is highly deserving of the Best Researcher Award for his outstanding contributions to remote sensing, mineral exploration, and geospatial data science. His innovative research—spanning hyperspectral image analysis, deep learning applications in mineral mapping, and environmental impact assessment—has significantly advanced the field while addressing pressing global challenges such as sustainable resource management and climate resilience. With a strong record of international publications, active peer-review service, and technical excellence, he exemplifies the qualities of a dedicated and impactful researcher. As he continues to expand his scholarly reach and takes on greater leadership roles, Mr. Habashi is well-positioned to become a prominent figure in Earth observation and environmental geoscience research on a global scale.
Publications Top Noted✍
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Title: PRISMA hyperspectral remote sensing data for mapping alteration minerals in Sar-e-Châh-e-Shur region, Birjand, Iran
Authors: J. Habashi, H. Jamshid Moghadam, M. Mohammady Oskouei, A.B. Pour, et al.
Year: 2024
Citations: 13 -
Title: Optimizing alteration mineral detection: A fusion of multispectral and hyperspectral remote sensing techniques in the Sar-e-Chah-e Shur, Iran
Authors: J. Habashi, M.M. Oskouei, H.J. Moghadam, A.B. Pour
Year: 2024
Citations: 10 -
Title: Classification of ASTER Data by Neural Network to Mapping Alterations Related to Copper and Iron Mineralization in Birjand
Authors: J. Habashi, M.M. Oskouei, H. Jamshid Moghadam
Year: 2024
Citations: 5 -
Title: Remote Sensing for Geophysicists
Authors: M. Gupta
Year: 2025
Citations: 1 -
Title: 19 Mineral Remote Identification Sensing Data Using
Authors: A.B. Pour, S. Niroomand, R. Lavaei, S. Mirzaee, J. Habashi, H.J. Moghadam
Year: 2025
Citations: 1 -
Title: Integration of ASTER imagery and field data for chromite exploration in the Eastern Khoy Ophiolite Complex, NW Iran
Authors: G. Nabatian, A. Songjian, A.B. Pour, F. Abdollahi, J. Habashi
Year: 2025
Citations: 1 -
Title: Recurrent-spectral convolutional neural networks (RecSpecCNN) architecture for hyperspectral lithological classification optimization
Authors: S. Hajaj, A.E. Harti, A.B. Pour, Y. Khandouch, N. Benaouiss, M. Hashim, J. Habashi, et al.
Year: 2025
Citations: 1 -
Title: Revealing critical mineralogical insights in extreme environments using deep learning technique on hyperspectral PRISMA satellite imagery: Dry Valleys, South Victoria Land, Antarctica
Authors: J. Habashi, A.B. Pour, A.M. Muslim, A.M. Afrapoli, J.K. Hong, Y. Park, A. Almasi, et al.
Year: 2025 -
Title: Mineral Identification Using Remote Sensing Data
Authors: A.B. Pour, S. Niroomand, R. Lavaei, S. Mirzaee, J. Habashi, H.J. Moghadam
Year: 2025 -
Title: Advancing Planetary Sustainability Through Lithological Mapping: ASTER Remote Sensing in Antarctica’s Dry Valleys
Authors: K. Riaz, A.B. Pour, A.M. Muslim, S. Khurram, J. Habashi