Nafiseh Kakhani | Soil Mapping | Best Researcher Award

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Dr. Nafiseh Kakhani | Soil Mapping | Best Researcher Award

Dr. Nafiseh Kakhani, Eberhard Karls University of Tübingen, Germany

Dr. Nafiseh Kakhani is a researcher and lecturer at Eberhard Karls University of Tübingen, Germany, specializing in Earth observation, remote sensing, and machine learning. She holds a PhD in Remote Sensing Engineering from K. N. Toosi University of Technology, Tehran, where she focused on spectral-spatial classification of high-resolution multispectral images. Her research interests include AI-driven geospatial analysis, explainable machine learning, digital soil mapping, and land cover classification. She has extensive experience in deep learning, computer vision, and statistical modeling for environmental applications. Dr. Kakhani has received prestigious awards, including the Best Poster Award at the 2023 IEEE IADF-GRSS School, and has published widely in her field.

Profile

Scopus

Summary:

Dr. Kakhani is a strong candidate for the Best Researcher Award due to her innovative contributions to explainable AI applications in soil science. Her interdisciplinary research and ability to integrate AI-driven approaches into environmental studies make her work highly relevant and impactful. She has contributed significantly to understanding soil organic carbon dynamics, a crucial factor in climate change mitigation and sustainable agriculture.

🎓 Education

Nafiseh Kakhani holds a PhD in Remote Sensing Engineering from K N Toosi University of Technology in Tehran, Iran, where she specialized in spectral-spatial classification of high-resolution multispectral images using segmentation methods. She completed her MSc in Remote Sensing Engineering from the same university, focusing on integrating neural networks and fuzzy systems to improve classification methods in hyperspectral images. She earned her BSc in Geomatics and Geodesy Engineering from the University of Isfahan, where she developed a statistical classification method for Multi-Beam Echo Sounder data.

💼Experience

She is currently an Earth Observation and Machine Learning Scientist at The LandBanking Group GmbH in Munich, where she applies machine learning techniques to environmental monitoring and land assessment. Previously, she was a Postdoctoral Researcher and Lecturer at the University of Tübingen, where she conducted research in remote sensing and taught courses on deep learning, photogrammetry, and the fundamentals of remote sensing. She has also worked at the Iranian Space Agency, focusing on remote sensing sensor calibration and spectral library preparation. Additionally, she has mentored Master’s students in GIS, remote sensing, and machine learning and has been a guest speaker at international workshops and conferences.

🔬Research Focus

Her research focuses on computer vision for Earth observation, explainable machine learning, deep learning, statistical machine learning, pattern recognition, and Earth system science. She has worked extensively on AI-driven geospatial analysis, digital soil mapping, land cover classification, and the development of deep learning frameworks for remote sensing applications.

🛠️Skills

She is proficient in Python, using libraries such as PyTorch, TensorFlow, and Scikit-learn, as well as MATLAB and JavaScript for Google Earth Engine applications. She has expertise in geospatial software, including ArcGIS, QGIS, ENVI, ERDAS IMAGINE, and Agisoft Metashape. She is experienced in cloud computing platforms such as Google Cloud, AWS, and Tübingen ML Cloud, enabling her to process large-scale remote sensing datasets efficiently.

🏆Awards

She received the Best Poster Award at the 2023 IEEE IADF-GRSS School for her work on SoilNet, a spatio-temporal deep learning framework for digital soil mapping. She was a top-ranked graduate student in both her MSc and BSc programs and was admitted to her MSc without an entrance exam, a privilege reserved for exceptional students in Iran.

📚 Publications

Publication: Towards Explainable AI: Interpreting Soil Organic Carbon Prediction Models Using a Learning-Based Explanation Method

Authors: N. Kakhani, R.T. Mehrjardi, D. Omarzadeh, U. Heiden, T.J. Scholten

Journal: European Journal of Soil Science

Year: 2025

Conclusion:

Dr. Nafiseh Kakhani is a highly suitable candidate for the Best Researcher Award. While there is always room for further growth, her expertise and achievements in applying AI to soil science place her among the leading researchers in this field.

Gang Yang | Soil Ecology | Best Researcher Award

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Prof. Dr. Gang Yang | Soil Ecology | Best Researcher Award

Prof. Dr. Gang Yang, Shaanxi university of science and technology, China

Prof. Dr. Gang Yang is a professor at Shaanxi University of Science and Technology, China, specializing in wetland carbon cycles, biogeochemistry, and global change ecology. With over 15 years of research, he has led multiple National Natural Science Foundation of China (NSFC) projects on peatland degradation, carbon sequestration, and greenhouse gas emissions. His work explores the role of semiconductor minerals in carbon cycling and the environmental responses of wetlands. A member of several ecological and environmental societies, he has an H-index of 23 and has published extensively in high-impact journals.

Profile

Orcid

Summary:

Prof. Dr. Gang Yang is a leading researcher in wetland ecology, carbon cycles, and biogeochemistry, with strong academic credentials, numerous high-impact publications, and significant research leadership. His innovative approaches to peatland carbon sequestration and degradation studies, along with his editorial and professional affiliations, make him an outstanding candidate for the Best Researcher Award.

🎓 Education

Gang Yang completed his Master’s degree in 2005 and has since been dedicated to research on soil carbon cycle processes and their environmental responses. His expertise spans soil ecology, ecosystem ecology, biogeochemistry, and global change ecology.

💼Experience

He is a Professor at Shaanxi University of Science and Technology and has been actively involved in wetland ecosystem carbon cycle research. He has served as the Principal Investigator for multiple National Natural Science Foundation of China (NSFC) projects, focusing on peatland degradation, carbon export mechanisms, and the role of semiconductor minerals in wetland carbon dynamics. His work also includes consultancy for the National Fourth Survey Project of Chinese Medicinal Plants.

🔬Research Focus

His research revolves around wetland carbon cycle mechanisms, wetland conservation and restoration, environmental responses of wetlands, and carbon sequestration in paddy fields. He has conducted extensive studies on peatlands in the Qinghai-Tibet Plateau, providing critical insights into carbon storage and greenhouse gas emissions in wetland ecosystems.

🛠️Skills

He has expertise in wetland carbon cycles, biogeochemical processes, and environmental impact assessments. His innovative research includes the use of isotope dating to study carbon accumulation in peatlands and the impact of climate change on carbon emissions. He has also proposed the dual effects of semiconductor minerals on the soil carbon cycle.

🏆Awards

Gang Yang has an H-index of 23, reflecting his significant impact in environmental science. He is a member of the Professional Committee on Wetland Environmental Ecological Conservation and Function Development of the Chinese Society for Environmental Sciences, the Shaanxi Ecological Society, the Sichuan Soil Society, and the International Peat Society.

📚 Publications

  • Falling water tables reduce peatland semiconductor minerals’ capacity for preserving carbon
    Year: 2024
    Author(s): Zeng J., Cao Q., Bai Y.P., Chen H., Liu M.X., He Y., He H.C., Hu W.Y., Yang G.*
    Journal: Land Degradation & Development

  • Soil pH and dissolved organic carbon shape microbial communities in wetlands with two different vegetation types in Changdu area, Tibet
    Year: 2023
    Author(s): Zou L., Bai Y.P., Huang J., Xiao D.R., Yang G.*
    Journal: Journal of Mountain Science

  • Water table drawdown increases plant biodiversity and soil polyphenol in the Zoige Plateau
    Year: 2021
    Author(s): Zeng J., Chen H., Bai Y., Dong F., Peng C., Yan F., Cao Q., Yang Z., Yang S., Yang G.*
    Journal: Ecological Indicators

  • Peatland degradation reduces methanogens and methane emissions from surface to deep soils
    Year: 2019
    Author(s): Yang G., Tian J., Chen H., Jiang L., Zhan W., Hu J.
    Journal: Ecological Indicators

  • Tiankeng: an ideal place for climate warming research on forest ecosystems
    Year: 2019
    Author(s): Yang G., Peng C., Liu Y., Dong F.
    Journal: Environmental Earth Sciences

  • Distribution characteristics, resource utilization and popularizing demonstration of crop straw in southwest China: A comprehensive evaluation
    Year: 2018
    Author(s): Yang G.
    Journal: Ecological Indicators

  • Interactive effect of radioactive and heavy-metal contamination on soil enzyme activity in a former Uranium mine
    Year: 2018
    Author(s): Yang G.
    Journal: Polish Journal of Environmental Studies

Conclusion:

 Prof. Dr. Gang Yang is highly deserving of the Best Researcher Award. Addressing broader international collaboration, policy engagement, and public outreach could further strengthen his influence and contributions to environmental science.