Federico Zangrando | Health Professions | Breakthrough Research Award Published on 21/04/2026 by Environmental Scientists After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 3386 Register Here
Haddou El Ghazi | Material sciences for PV | Editorial Board Member Published on 18/04/2026 by Environmental Scientists After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 3012 Register Here
Ozge Sizmaz | Animal Nutrition | Editorial Board Member Published on 18/04/2026 by Environmental Scientists After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 2984 Register Here
Anam Farzand | Health Professions | Editorial Board Member Published on 18/04/202618/04/2026 by Environmental Scientists After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 2961 Register Here
Muhammad Latzaz Ul Hassan | Management and Accounting | Research Excellence Award Published on 15/04/2026 by Environmental Scientists After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 3383 Register Here
Mingxing Jia | Artificial Neural Networks | Research Excellence Distinction Award Published on 10/04/202610/04/2026 by Environmental Scientists After Completing the Registration Process, your Biography will be displayed here. Register by using your Entry ID: 3381 Register Here
Vivek Dwivedi | Computer Science | Research Excellence Award Published on 10/04/2026 by Environmental Scientists Mr. Vivek Dwivedi | Computer Science | Research Excellence Award Research Scholar | The University of Slovak University of Technology | Slovakia Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Mr. Vivek Dwivedi is an emerging researcher in the field of Computer Science, specializing in machine learning, robotics, and intelligent computational systems. His research emphasizes the development of real-time applications using computer vision, natural language processing, and advanced programming frameworks. He has worked on innovative solutions such as adaptive multi-camera systems for virtual environments and intelligent robotic mechanisms, showcasing strong technical expertise and research potential. With 12 published documents, 25 citations, and an h-index of 3, his contributions reflect steady academic growth and relevance. His work aims to bridge the gap between theoretical research and practical implementation, contributing to advancements in automation, smart technologies, and next-generation digital systems that address real-world challenges. Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index View Scopus Profile View Google Scholar Profile View Research Gate Profile Featured Publications Comprehensive Electric Load Forecasting Using Ensemble Machine Learning Methods – ICSSIP, 2022 (Cited by 8) Multiple-Camera System for 3D Object Detection in Virtual Environment Using Intelligent Approach – ICSSIP, 2022 (Cited by 7) Short-Term Electric Load Forecast Model Using Ant Lion Optimization with Bi-LSTM Network – ICSSIP, 2023 (Cited by 6) Automatic Image Stitching for Stereo Spherical Image – ELMAR Symposium, 2022 (Cited by 4)
Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index
Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index
Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index
Citation Metrics ( Scopus ) 60 50 40 30 20 10 0 Citations 25 documents 12 h-index 3 Citations Documents h-index
Abdulaziz Abahussain | Chemical Engineering | Research Excellence Award Published on 09/04/2026 by Environmental Scientists Assoc. Prof. Dr. Abdulaziz Abahussain | Chemical Engineering | Research Excellence Award Associate Professor | The University of King Saud University | Saudi Arabia Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Assoc. Prof. Dr. Abdulaziz A. M. Aba Hussain is an accomplished researcher in chemical engineering, specializing in electrochemical engineering, catalysis, and renewable energy systems. His research encompasses hydrogen production technologies, direct borohydride fuel cells, CO₂ utilization, and advanced nanocatalysts for sustainable energy applications. With a strong academic record of 55 publications, 395 citations, and an h-index of 13, his work significantly contributes to improving energy conversion efficiency and environmental sustainability. His studies combine theoretical modeling, simulation, and experimental validation to address critical challenges in fuel cells, electrolysis, and catalytic reactions. Through his research, he actively supports the transition toward low-carbon energy systems and the development of cost-effective, high-performance electrochemical technologies for industrial and environmental applications. Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Samarium Promoted Ni-Catalyst Dispersed Over Yttria-Zirconia for H₂-Rich Syngas Production Through Partial Oxidation of Methane – Molecular Catalysis, 2026 Nickel-Based Catalysts for Hydrogen Production Through Partial Oxidation: The Role of KIT-6 and Promoter Effects – Catalysts, 2026 Impact of Rh, La, Sm, and Au on Ni/Al₂O₃ Catalysts in Dry Reforming of Methane for Syngas Production – Research on Chemical Intermediates, 2026 Effect of Promoters on Co/Al₂O₃ Catalysts for Partial Oxidation of Methane: Structure–Activity Correlations – Catalysts, 2025 Benchmarking Key Performance Factors in Textile Industry Effluent Treatment Processes for Enhanced Environmental Remediation – Scientific Reports, 2024
Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index
Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index
Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index
Citation Metrics ( Scopus ) 600 500 400 300 200 100 0 Citations 395 documents 52 h-index 13 Citations Documents h-index
View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications
Ali Danandeh Mehr | Environmental Science | Best Researcher Award Published on 09/04/202609/04/2026 by Environmental Scientists Prof. Dr. Ali Danandeh Mehr | Environmental Science | Best Researcher Award Professor | The University of Antalya Bilim University | Turkey Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Prof. Dr. Ali Danandeh Mehr is a prominent scholar in civil and environmental engineering, specializing in hydrology, drought modeling, and climate variability. His research integrates cutting-edge computational approaches such as machine learning, genetic programming, and hybrid data-driven models to solve complex water-related challenges. He has published 115 scientific documents in reputed international journals, advancing the field of hydroinformatics and predictive environmental modeling. With 4,186 citations and an h-index of 37, his research reflects significant global impact and scholarly recognition. His work focuses on understanding extreme climatic events, improving forecasting accuracy, and supporting sustainable water resource planning. Through innovative methodologies and interdisciplinary approaches, his contributions continue to enhance resilience and decision-making in water resources engineering and environmental sustainability. Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Assessing Seasonal Drought Persistence Using a Bayesian Logistic Regression Approach – Physics and Chemistry of the Earth, 2026 BAMPP: A Novel Bayesian Network Enhanced by Average Marginal Posterior Probabilities for Drought Monitoring – Physics and Chemistry of the Earth, 2026 Meteorological Drought Modeling Using Recurrent Neural Network and Long Short-Term Memory – Book Chapter Time-Dependent Intrinsic Correlation Analysis of Climatic Oscillations and Extreme Indices – Atmosphere, 2025 Multi-Level Trend Analysis of Extreme Climate Indices Using Hybrid Fuzzy Logic Methods – Scientific Reports, 2025
Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index
Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index
Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index
Citation Metrics ( Scopus ) 6000 5000 4000 3000 2000 1000 0 Citations 4186 documents 115 h-index 37 Citations Documents h-index
Naji Al-Dosary | Agricultural and Biological Sciences | Research Excellence Award Published on 09/04/2026 by Environmental Scientists Prof. Naji Al-Dosary | Agricultural and Biological Sciences | Research Excellence Award Professor | The University of King Saud University | Saudi Arabia Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Dr. Naji Al-Dosary is an accomplished researcher specializing in Agricultural and Biological Engineering, with expertise in machine development, harvesting systems, and precision agriculture technologies. His research emphasizes the design and optimization of agricultural machinery, including innovative harvesting equipment and fluid power systems, alongside applications of GIS and GPS for improved farm management. He has significantly contributed to advancing post-harvest operations and reducing crop losses through engineering solutions. With 16 publications, 224 citations, and an h-index of 7, his scholarly impact highlights consistent contributions to agricultural engineering research. His work bridges theory and application, supporting sustainable farming practices and enhancing productivity through mechanization and smart agricultural technologies. Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications Review on the Management of Red Palm Weevil (Rhynchophorus ferrugineus) in Date Palm (Phoenix dactylifera L) – Emirates Journal of Food and Agriculture, 2016 Potato Harvester Performance on Tuber Damage in Eastern Saudi Arabia – Agricultural Engineering International: CIGR Journal, 2016 K-Nearest Neighbors Method for Prediction of Fuel Consumption in Tractor–Chisel Plow Systems – Engenharia Agrícola, 2019 Evaluation of Soil Characteristics for Agricultural Machinery Management in Al Aflaj Oasis, Saudi Arabia – Sustainability, 2022 Estimation of Wheel Slip in 2WD Mode for Agricultural Tractor Using Artificial Neural Networks – Scientific Reports, 2023
Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index
Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index
Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index
Citation Metrics ( Scopus ) 300 250 200 150 100 50 0 Citations 224 documents 16 h-index 7 Citations Documents h-index
View Scopus Profile View ORCID Profile View Google Scholar Profile View Research Gate Profile Featured Publications