Hatem Magdy Keshk | Computer Science | Best Researcher Award Published on 09/09/202509/09/2025 by World Top Scientists Assist. Prof. Dr. Hatem Magdy Keshk | Computer Science | Best Researcher Award Postdoc at King Fahd University of Petroleum and Minerals | Saudi Arabia Dr. Hatem Magdy Keshk is an accomplished researcher and academic with extensive expertise in artificial intelligence, deep learning, remote sensing, satellite image processing, GIS, UAV applications, and smart cities. He has served in diverse academic and research roles, including teaching, curriculum development, and departmental leadership, while also conducting impactful research across multiple disciplines. His career spans leading institutions in Egypt, Saudi Arabia, and Hong Kong, where he has undertaken postdoctoral research in interdisciplinary and space-related fields. Beyond academia, he has contributed to national and international initiatives such as land cover classification for Arab countries and served as a member of research councils, reflecting his commitment to advancing both science and societal applications. With over a decade of experience in teaching and research, he continues to blend innovation with academic rigor, positioning himself as a valuable contributor to the global research community and a strong candidate for recognition Professional Profile Google Scholar | Scopus Profile | ORCID Profile Education Dr. Hatem Magdy Keshk has pursued an extensive academic journey in computer science and related fields, equipping himself with strong theoretical knowledge and practical expertise. His educational background is highlighted by a Postdoctoral Fellowship at The Hong Kong Polytechnic University, where he conducted interdisciplinary research at the Smart Cities Research Institute. He later advanced his postdoctoral work at King Fahd University of Petroleum and Minerals, focusing on artificial intelligence, deep learning, and UAV applications under the Interdisciplinary Research Center for Aviation and Space Exploration. Throughout his academic development, he has engaged in both teaching and research simultaneously, ensuring that his educational growth was complemented by practical exposure. This balanced foundation has enabled him to develop expertise in machine learning, programming, image processing, and networking, while also gaining international research exposure that broadened his perspective on addressing global scientific challenges through interdisciplinary approaches. Experience Dr. Hatem Magdy Keshk has accumulated extensive professional experience spanning over a decade across teaching, research, and academic leadership. He began his career as a teaching assistant and coordinator in computer science, where he managed courses, laboratories, and departmental coordination. His academic career includes teaching positions at leading Egyptian institutions such as Future University, Obour Institute, and others, where he taught a wide range of subjects from artificial intelligence to operating systems and GIS. Beyond teaching, he has played a significant role in research, serving as a researcher at the National Authority for Remote Sensing and Space Sciences, where he worked on satellite image analysis, GIS applications, and deep learning integration. His experience also extends internationally, with postdoctoral research at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals. These roles highlight his ability to blend teaching, research, and applied science, contributing to both academia and national projects. Research Focus The research of Dr. Hatem Magdy Keshk lies at the intersection of artificial intelligence, deep learning, and remote sensing, with strong applications in smart cities, UAV systems, and space exploration. His work has concentrated on developing algorithms and systems for processing and analyzing satellite images, contributing to fields such as land cover classification and environmental monitoring. By combining AI with geospatial technologies, his research aims to create efficient solutions for large-scale data analysis and decision support systems. He has also contributed to the advancement of UAV applications, integrating machine learning techniques for enhanced automation and real-world usability. His interdisciplinary approach extends to smart city development, where his work supports sustainable urban planning and technology-driven innovation. With contributions spanning data science, computer vision, and applied AI, his research not only strengthens academic knowledge but also provides solutions with societal and industrial impact, positioning him as a versatile and impactful researcher. Award and Honor Dr. Hatem Magdy Keshk has earned recognition for his sustained contributions to research, teaching, and academic service. His selection for prestigious postdoctoral fellowships at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals reflects international acknowledgment of his expertise and research potential. His involvement in high-level councils, including the Space Research Council under Egypt’s Ministry of Research and Higher Education, further highlights his standing as a respected contributor to national scientific initiatives. Additionally, his participation in globally significant programs, such as the FAO Land Cover Classification System for Arab countries, underscores the trust placed in his capabilities to contribute to large-scale, impactful projects. These honors, alongside his leadership roles in academic departments and curriculum development, showcase not only his research excellence but also his dedication to advancing education and interdisciplinary collaboration. Collectively, these achievements underline his status as a researcher of high merit. Publication Top Notes Title: Satellite super-resolution images depending on deep learning methods: a comparative studyYear: 2017Citations: 24 Title: Change detection in SAR images based on deep learningYear: 2020Citations: 22 Title: Performance evaluation of quality measurement for super-resolution satellite imagesYear: 2014Citations: 16 Title: Obtaining super-resolution satellites images based on enhancement deep convolutional neural networkAuthors: HM Keshk, XC YinYear: 2021Citations: 11 Title: Semantic segmentation of some rock-forming mineral thin sections using deep learning algorithms: a case study from the Nikeiba area, South Eastern Desert, EgyptYear: 2024Citations: 8 Title: Classification of EgyptSat-1 images using deep learning methodsYear: 2020Citations: 8 Title: Three-pass (DInSAR) ground change detection in Sukari gold mine, Eastern Desert, EgyptYear: 2022Citations: 4 Title: Geometric Correction of Aerial Camera and LiDAR Hybrid System Data Using GNSS/IMUYear: 2022Citations: 2 Title: Retracted article: Sentinel-2 cloud mask classification using deep learning methodYear: 2022Citations: 2 Conclusion Dr. Hatem Magdy Keshk has made significant contributions to the fields of artificial intelligence, deep learning, and remote sensing, with a strong focus on satellite image processing, change detection, and smart applications in geosciences and urban development. His publications demonstrate a blend of theoretical advancements and practical applications, contributing to international research visibility. With impactful works published in respected journals and conferences, his research has attracted citations that reflect the recognition of his contributions within the scientific community. Despite one retracted paper, the overall body of his work shows consistency, innovation, and interdisciplinary application. His role as both a researcher and collaborator highlights his ability to address complex scientific challenges and develop solutions of societal and technological value. These accomplishments position him as a strong candidate for honors such as the Best Researcher Award, with ongoing potential to expand his impact globally.
Dr. Hatem Magdy Keshk is an accomplished researcher and academic with extensive expertise in artificial intelligence, deep learning, remote sensing, satellite image processing, GIS, UAV applications, and smart cities. He has served in diverse academic and research roles, including teaching, curriculum development, and departmental leadership, while also conducting impactful research across multiple disciplines. His career spans leading institutions in Egypt, Saudi Arabia, and Hong Kong, where he has undertaken postdoctoral research in interdisciplinary and space-related fields. Beyond academia, he has contributed to national and international initiatives such as land cover classification for Arab countries and served as a member of research councils, reflecting his commitment to advancing both science and societal applications. With over a decade of experience in teaching and research, he continues to blend innovation with academic rigor, positioning himself as a valuable contributor to the global research community and a strong candidate for recognition Professional Profile Google Scholar | Scopus Profile | ORCID Profile Education Dr. Hatem Magdy Keshk has pursued an extensive academic journey in computer science and related fields, equipping himself with strong theoretical knowledge and practical expertise. His educational background is highlighted by a Postdoctoral Fellowship at The Hong Kong Polytechnic University, where he conducted interdisciplinary research at the Smart Cities Research Institute. He later advanced his postdoctoral work at King Fahd University of Petroleum and Minerals, focusing on artificial intelligence, deep learning, and UAV applications under the Interdisciplinary Research Center for Aviation and Space Exploration. Throughout his academic development, he has engaged in both teaching and research simultaneously, ensuring that his educational growth was complemented by practical exposure. This balanced foundation has enabled him to develop expertise in machine learning, programming, image processing, and networking, while also gaining international research exposure that broadened his perspective on addressing global scientific challenges through interdisciplinary approaches. Experience Dr. Hatem Magdy Keshk has accumulated extensive professional experience spanning over a decade across teaching, research, and academic leadership. He began his career as a teaching assistant and coordinator in computer science, where he managed courses, laboratories, and departmental coordination. His academic career includes teaching positions at leading Egyptian institutions such as Future University, Obour Institute, and others, where he taught a wide range of subjects from artificial intelligence to operating systems and GIS. Beyond teaching, he has played a significant role in research, serving as a researcher at the National Authority for Remote Sensing and Space Sciences, where he worked on satellite image analysis, GIS applications, and deep learning integration. His experience also extends internationally, with postdoctoral research at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals. These roles highlight his ability to blend teaching, research, and applied science, contributing to both academia and national projects. Research Focus The research of Dr. Hatem Magdy Keshk lies at the intersection of artificial intelligence, deep learning, and remote sensing, with strong applications in smart cities, UAV systems, and space exploration. His work has concentrated on developing algorithms and systems for processing and analyzing satellite images, contributing to fields such as land cover classification and environmental monitoring. By combining AI with geospatial technologies, his research aims to create efficient solutions for large-scale data analysis and decision support systems. He has also contributed to the advancement of UAV applications, integrating machine learning techniques for enhanced automation and real-world usability. His interdisciplinary approach extends to smart city development, where his work supports sustainable urban planning and technology-driven innovation. With contributions spanning data science, computer vision, and applied AI, his research not only strengthens academic knowledge but also provides solutions with societal and industrial impact, positioning him as a versatile and impactful researcher. Award and Honor Dr. Hatem Magdy Keshk has earned recognition for his sustained contributions to research, teaching, and academic service. His selection for prestigious postdoctoral fellowships at The Hong Kong Polytechnic University and King Fahd University of Petroleum and Minerals reflects international acknowledgment of his expertise and research potential. His involvement in high-level councils, including the Space Research Council under Egypt’s Ministry of Research and Higher Education, further highlights his standing as a respected contributor to national scientific initiatives. Additionally, his participation in globally significant programs, such as the FAO Land Cover Classification System for Arab countries, underscores the trust placed in his capabilities to contribute to large-scale, impactful projects. These honors, alongside his leadership roles in academic departments and curriculum development, showcase not only his research excellence but also his dedication to advancing education and interdisciplinary collaboration. Collectively, these achievements underline his status as a researcher of high merit. Publication Top Notes Title: Satellite super-resolution images depending on deep learning methods: a comparative studyYear: 2017Citations: 24 Title: Change detection in SAR images based on deep learningYear: 2020Citations: 22 Title: Performance evaluation of quality measurement for super-resolution satellite imagesYear: 2014Citations: 16 Title: Obtaining super-resolution satellites images based on enhancement deep convolutional neural networkAuthors: HM Keshk, XC YinYear: 2021Citations: 11 Title: Semantic segmentation of some rock-forming mineral thin sections using deep learning algorithms: a case study from the Nikeiba area, South Eastern Desert, EgyptYear: 2024Citations: 8 Title: Classification of EgyptSat-1 images using deep learning methodsYear: 2020Citations: 8 Title: Three-pass (DInSAR) ground change detection in Sukari gold mine, Eastern Desert, EgyptYear: 2022Citations: 4 Title: Geometric Correction of Aerial Camera and LiDAR Hybrid System Data Using GNSS/IMUYear: 2022Citations: 2 Title: Retracted article: Sentinel-2 cloud mask classification using deep learning methodYear: 2022Citations: 2 Conclusion Dr. Hatem Magdy Keshk has made significant contributions to the fields of artificial intelligence, deep learning, and remote sensing, with a strong focus on satellite image processing, change detection, and smart applications in geosciences and urban development. His publications demonstrate a blend of theoretical advancements and practical applications, contributing to international research visibility. With impactful works published in respected journals and conferences, his research has attracted citations that reflect the recognition of his contributions within the scientific community. Despite one retracted paper, the overall body of his work shows consistency, innovation, and interdisciplinary application. His role as both a researcher and collaborator highlights his ability to address complex scientific challenges and develop solutions of societal and technological value. These accomplishments position him as a strong candidate for honors such as the Best Researcher Award, with ongoing potential to expand his impact globally.
Dr. Hatem Magdy Keshk has made significant contributions to the fields of artificial intelligence, deep learning, and remote sensing, with a strong focus on satellite image processing, change detection, and smart applications in geosciences and urban development. His publications demonstrate a blend of theoretical advancements and practical applications, contributing to international research visibility. With impactful works published in respected journals and conferences, his research has attracted citations that reflect the recognition of his contributions within the scientific community. Despite one retracted paper, the overall body of his work shows consistency, innovation, and interdisciplinary application. His role as both a researcher and collaborator highlights his ability to address complex scientific challenges and develop solutions of societal and technological value. These accomplishments position him as a strong candidate for honors such as the Best Researcher Award, with ongoing potential to expand his impact globally.
Baha Ihnaini | Computer Science | Outstanding Contribution Award Published on 28/08/202528/08/2025 by World Top Scientists Dr. Baha Ihnaini | Computer Science | Outstanding Contribution Award Assistant Professor at Wenzhou-Kean University, China Dr. Baha Ihnaini is an accomplished academic and researcher in computer science with expertise spanning artificial intelligence, data science, machine learning, and natural language processing. His scholarly work has addressed significant challenges in sentiment analysis, medical diagnostics, disease prediction, and misinformation detection, with publications in respected journals and international conferences. Notably, he has contributed to developing Arabic lexicons for sentiment analysis, enhancing AI-driven healthcare solutions, and advancing transfer learning models for predictive analytics. Alongside his research, Dr. Ihnaini has demonstrated a strong commitment to teaching, covering a wide range of computer science courses and mentoring students in senior projects. His service on academic committees and involvement in curriculum development highlight his leadership and dedication to institutional growth. With a record of impactful research, effective teaching, and professional service, Dr. Ihnaini stands out as a valuable contributor to his field and a strong candidate for academic recognition. Professional Profile Google Scholar | Scopus Profile | ORCID Profile Education Dr. Baha Ihnaini holds a Ph.D. in Computer Science with a specialization in Data Science from Universiti Utara Malaysia, where his research focused on developing an expandable Arabic lexicon and sentiment analysis rules for social media text. He also earned a Master of Science in Management Information Systems from The Arab Academy for Banking and Financial Sciences, equipping him with a strong foundation in both technical and managerial aspects of information technology. His academic journey began with a Bachelor’s degree in Computer Engineering from Philadelphia University in Jordan, providing him with comprehensive knowledge of hardware, software, and systems engineering. This multidisciplinary educational background has enabled Dr. Ihnaini to integrate advanced computational methods with practical problem-solving approaches, particularly in the areas of machine learning, natural language processing, and data-driven applications. His academic credentials reflect a balance between rigorous technical expertise and applied research in emerging fields of computing. Experience Dr. Ihnaini has accumulated rich professional experience as an educator, researcher, and academic leader across several institutions. He currently serves as an Assistant Professor of Computer Science at Wenzhou-Kean University, where he teaches a broad range of courses, from foundational programming and systems to advanced research in computer science. His roles extend beyond teaching, as he actively contributes to academic committees focused on curriculum development, faculty hiring, and student support. Prior to this, he served as an Adjunct Professor at Al Ain University and BTEC Abu Dhabi, as well as a Lecturer at Al Khawarizmi International College, where he guided student projects and curriculum design. Earlier in his career, he worked as a Research Officer at Universiti Utara Malaysia’s InterNetWorks Research Lab, where he played a pivotal role in advancing sentiment analysis for Arabic text. Collectively, his experience reflects a strong commitment to research, teaching excellence, and academic service. Research Focus Dr. Ihnaini’s research focuses on artificial intelligence, machine learning, data science, and natural language processing, with an emphasis on solving real-world problems through intelligent systems. A significant part of his work has concentrated on Arabic sentiment analysis, where he developed innovative linguistic resources and computational models to improve text classification accuracy. His recent research extends to medical AI, including predictive modeling for diseases such as diabetic retinopathy, Alzheimer’s disease, and vitamin D deficiency, showcasing his ability to merge computer science with healthcare applications. He has also contributed to the advancement of fake news detection, stock market prediction using sentiment data, and multimodal semantic similarity. His interdisciplinary approach highlights the versatility of data-driven methods and their societal impact, from enhancing healthcare systems to improving digital communication analysis. Through these diverse but interconnected research directions, Dr. Ihnaini continues to contribute to both theoretical advancements and practical innovations in computer science. Award and Honor Dr. Ihnaini has earned recognition for his scholarly contributions through research publications in reputable international journals and conferences, with several works indexed in Scopus and well-regarded platforms. His achievements include developing novel computational methods for sentiment analysis, interdisciplinary research in healthcare prediction models, and the application of advanced machine learning techniques to real-world problems. His role as a key contributor to collaborative projects with international researchers further reflects the recognition of his expertise and the impact of his work. Beyond research, his commitment to education and service has been acknowledged within the institutions he has served, particularly through his involvement in curriculum innovation and student mentorship. While formal distinctions are highlighted through his publication record and conference participation, his career trajectory itself demonstrates consistent recognition as a capable scholar and educator. His growing research visibility and international collaborations continue to strengthen his candidacy for prestigious awards and honors. Publication Top Notes Title: A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learningAuthors: B Ihnaini, MA Khan, TA Khan, S Abbas, MS Daoud, M Ahmad, MA KhanYear: 2021Citations: 158 Title: Machine Learning Empowered Software Defect Prediction SystemAuthors: MS Daoud, S Aftab, M Ahmad, MA Khan, A Iqbal, S Abbas, M Iqbal, B IhnainiYear: 2022Citations: 37 Title: Stock trend prediction using sentiment analysisAuthors: Q Xiao, B IhnainiYear: 2023Citations: 35 Title: Joint channel and multi-user detection empowered with machine learningAuthors: MS Daoud, A Fatima, WA Khan, MA Khan, S Abbas, B Ihnaini, M AhmadYear: 2021Citations: 31 Title: Real-time shill bidding fraud detection empowered with fussed machine learningAuthors: WUH Abidi, MS Daoud, B Ihnaini, MA Khan, T Alyas, A Fatima, M AhmadYear: 2021Citations: 28 Title: Rider weed deep residual network-based incremental model for text classification using multidimensional features and MapReduceAuthors: HB Abdalla, AM Ahmed, SRM Zeebaree, A Alkhayyat, B IhnainiYear: 2022Citations: 18 Title: Presenting and evaluating scaled extreme programming process modelAuthors: M Ibrahim, S Aftab, M Ahmad, A Iqbal, BS Khan, M Iqbal, BNS IhnainiYear: 2020Citations: 13 Title: Exploring the agile family: A surveyAuthors: M Ibrahim, S Aftab, B Bakhtawar, M Ahmad, A Iqbal, N Aziz, MS Javeid, B IhnainiYear: 2020Citations: 12 Title: Predicting vitamin D deficiency using optimized random forest classifierAuthors: A Alloubani, B Abuhaija, M Almatari, G Jaradat, B IhnainiYear: 2024Citations: 9 Title: Lexicon-based sentiment analysis of Arabic tweets: A surveyAuthors: B Ihnaini, M MahmuddinYear: 2018Citations: 9 Title: A Severity Grading Framework for Diabetic Retinopathy Detection using Transfer LearningAuthors: S Akhtar, S Aftab, S Kousar, A Rehman, M Ahmad, AQ Saeed, B IhnainiYear: 2024Citations: 8 Title: Improving the Quality of e-Commerce Service by Implementing Combination Models with Step-by-Step, Bottom-Up ApproachAuthors: BA Hemn, G Chengwei, B IhnainiYear: 2021Citations: 6 Title: Sentiment analysis of Song Dynasty classical poetry using fine-tuned large language models: a study with LLMsAuthors: B Ihnaini, W Sun, Y Cai, Z Xu, R SangiYear: 2024Citations: 5 Title: A transfer learning based framework for diabetic retinopathy detection using data fusionAuthors: S Akhtar, S Aftab, M Ahmad, B IhnainiYear: 2024Citations: 4 Title: Semantic similarity on multimodal data: A comprehensive survey with applicationsAuthors: B Ihnaini, B Abuhaija, EA Mills, M MahmuddinYear: 2024Citations: 3 Conclusion Dr. Baha Ihnaini’s publication record reflects a strong and steadily growing research trajectory across diverse yet interconnected fields of computer science, including artificial intelligence, data science, natural language processing, and medical informatics. His works demonstrate both theoretical depth and practical applications, ranging from healthcare prediction models and fraud detection to sentiment analysis and software engineering. The high citation impact of certain publications highlights the relevance and influence of his research in the academic community, while his more recent works indicate an expanding focus on interdisciplinary applications such as healthcare and cultural text analysis using advanced AI techniques. Collectively, his contributions showcase a balance of innovation, collaboration, and societal relevance, positioning him as a researcher whose work is not only academically significant but also impactful in addressing real-world challenges. This combination of influence, diversity, and practical value strengthens his candidacy for recognition through awards and honors.
Dr. Baha Ihnaini is an accomplished academic and researcher in computer science with expertise spanning artificial intelligence, data science, machine learning, and natural language processing. His scholarly work has addressed significant challenges in sentiment analysis, medical diagnostics, disease prediction, and misinformation detection, with publications in respected journals and international conferences. Notably, he has contributed to developing Arabic lexicons for sentiment analysis, enhancing AI-driven healthcare solutions, and advancing transfer learning models for predictive analytics. Alongside his research, Dr. Ihnaini has demonstrated a strong commitment to teaching, covering a wide range of computer science courses and mentoring students in senior projects. His service on academic committees and involvement in curriculum development highlight his leadership and dedication to institutional growth. With a record of impactful research, effective teaching, and professional service, Dr. Ihnaini stands out as a valuable contributor to his field and a strong candidate for academic recognition. Professional Profile Google Scholar | Scopus Profile | ORCID Profile Education Dr. Baha Ihnaini holds a Ph.D. in Computer Science with a specialization in Data Science from Universiti Utara Malaysia, where his research focused on developing an expandable Arabic lexicon and sentiment analysis rules for social media text. He also earned a Master of Science in Management Information Systems from The Arab Academy for Banking and Financial Sciences, equipping him with a strong foundation in both technical and managerial aspects of information technology. His academic journey began with a Bachelor’s degree in Computer Engineering from Philadelphia University in Jordan, providing him with comprehensive knowledge of hardware, software, and systems engineering. This multidisciplinary educational background has enabled Dr. Ihnaini to integrate advanced computational methods with practical problem-solving approaches, particularly in the areas of machine learning, natural language processing, and data-driven applications. His academic credentials reflect a balance between rigorous technical expertise and applied research in emerging fields of computing. Experience Dr. Ihnaini has accumulated rich professional experience as an educator, researcher, and academic leader across several institutions. He currently serves as an Assistant Professor of Computer Science at Wenzhou-Kean University, where he teaches a broad range of courses, from foundational programming and systems to advanced research in computer science. His roles extend beyond teaching, as he actively contributes to academic committees focused on curriculum development, faculty hiring, and student support. Prior to this, he served as an Adjunct Professor at Al Ain University and BTEC Abu Dhabi, as well as a Lecturer at Al Khawarizmi International College, where he guided student projects and curriculum design. Earlier in his career, he worked as a Research Officer at Universiti Utara Malaysia’s InterNetWorks Research Lab, where he played a pivotal role in advancing sentiment analysis for Arabic text. Collectively, his experience reflects a strong commitment to research, teaching excellence, and academic service. Research Focus Dr. Ihnaini’s research focuses on artificial intelligence, machine learning, data science, and natural language processing, with an emphasis on solving real-world problems through intelligent systems. A significant part of his work has concentrated on Arabic sentiment analysis, where he developed innovative linguistic resources and computational models to improve text classification accuracy. His recent research extends to medical AI, including predictive modeling for diseases such as diabetic retinopathy, Alzheimer’s disease, and vitamin D deficiency, showcasing his ability to merge computer science with healthcare applications. He has also contributed to the advancement of fake news detection, stock market prediction using sentiment data, and multimodal semantic similarity. His interdisciplinary approach highlights the versatility of data-driven methods and their societal impact, from enhancing healthcare systems to improving digital communication analysis. Through these diverse but interconnected research directions, Dr. Ihnaini continues to contribute to both theoretical advancements and practical innovations in computer science. Award and Honor Dr. Ihnaini has earned recognition for his scholarly contributions through research publications in reputable international journals and conferences, with several works indexed in Scopus and well-regarded platforms. His achievements include developing novel computational methods for sentiment analysis, interdisciplinary research in healthcare prediction models, and the application of advanced machine learning techniques to real-world problems. His role as a key contributor to collaborative projects with international researchers further reflects the recognition of his expertise and the impact of his work. Beyond research, his commitment to education and service has been acknowledged within the institutions he has served, particularly through his involvement in curriculum innovation and student mentorship. While formal distinctions are highlighted through his publication record and conference participation, his career trajectory itself demonstrates consistent recognition as a capable scholar and educator. His growing research visibility and international collaborations continue to strengthen his candidacy for prestigious awards and honors. Publication Top Notes Title: A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learningAuthors: B Ihnaini, MA Khan, TA Khan, S Abbas, MS Daoud, M Ahmad, MA KhanYear: 2021Citations: 158 Title: Machine Learning Empowered Software Defect Prediction SystemAuthors: MS Daoud, S Aftab, M Ahmad, MA Khan, A Iqbal, S Abbas, M Iqbal, B IhnainiYear: 2022Citations: 37 Title: Stock trend prediction using sentiment analysisAuthors: Q Xiao, B IhnainiYear: 2023Citations: 35 Title: Joint channel and multi-user detection empowered with machine learningAuthors: MS Daoud, A Fatima, WA Khan, MA Khan, S Abbas, B Ihnaini, M AhmadYear: 2021Citations: 31 Title: Real-time shill bidding fraud detection empowered with fussed machine learningAuthors: WUH Abidi, MS Daoud, B Ihnaini, MA Khan, T Alyas, A Fatima, M AhmadYear: 2021Citations: 28 Title: Rider weed deep residual network-based incremental model for text classification using multidimensional features and MapReduceAuthors: HB Abdalla, AM Ahmed, SRM Zeebaree, A Alkhayyat, B IhnainiYear: 2022Citations: 18 Title: Presenting and evaluating scaled extreme programming process modelAuthors: M Ibrahim, S Aftab, M Ahmad, A Iqbal, BS Khan, M Iqbal, BNS IhnainiYear: 2020Citations: 13 Title: Exploring the agile family: A surveyAuthors: M Ibrahim, S Aftab, B Bakhtawar, M Ahmad, A Iqbal, N Aziz, MS Javeid, B IhnainiYear: 2020Citations: 12 Title: Predicting vitamin D deficiency using optimized random forest classifierAuthors: A Alloubani, B Abuhaija, M Almatari, G Jaradat, B IhnainiYear: 2024Citations: 9 Title: Lexicon-based sentiment analysis of Arabic tweets: A surveyAuthors: B Ihnaini, M MahmuddinYear: 2018Citations: 9 Title: A Severity Grading Framework for Diabetic Retinopathy Detection using Transfer LearningAuthors: S Akhtar, S Aftab, S Kousar, A Rehman, M Ahmad, AQ Saeed, B IhnainiYear: 2024Citations: 8 Title: Improving the Quality of e-Commerce Service by Implementing Combination Models with Step-by-Step, Bottom-Up ApproachAuthors: BA Hemn, G Chengwei, B IhnainiYear: 2021Citations: 6 Title: Sentiment analysis of Song Dynasty classical poetry using fine-tuned large language models: a study with LLMsAuthors: B Ihnaini, W Sun, Y Cai, Z Xu, R SangiYear: 2024Citations: 5 Title: A transfer learning based framework for diabetic retinopathy detection using data fusionAuthors: S Akhtar, S Aftab, M Ahmad, B IhnainiYear: 2024Citations: 4 Title: Semantic similarity on multimodal data: A comprehensive survey with applicationsAuthors: B Ihnaini, B Abuhaija, EA Mills, M MahmuddinYear: 2024Citations: 3 Conclusion Dr. Baha Ihnaini’s publication record reflects a strong and steadily growing research trajectory across diverse yet interconnected fields of computer science, including artificial intelligence, data science, natural language processing, and medical informatics. His works demonstrate both theoretical depth and practical applications, ranging from healthcare prediction models and fraud detection to sentiment analysis and software engineering. The high citation impact of certain publications highlights the relevance and influence of his research in the academic community, while his more recent works indicate an expanding focus on interdisciplinary applications such as healthcare and cultural text analysis using advanced AI techniques. Collectively, his contributions showcase a balance of innovation, collaboration, and societal relevance, positioning him as a researcher whose work is not only academically significant but also impactful in addressing real-world challenges. This combination of influence, diversity, and practical value strengthens his candidacy for recognition through awards and honors.