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 

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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 study
  Year: 2017
  Citations: 24

• Title: Change detection in SAR images based on deep learning
  Year: 2020
  Citations: 22

• Title: Performance evaluation of quality measurement for super-resolution satellite images
  Year: 2014
  Citations: 16

• Title: Obtaining super-resolution satellites images based on enhancement deep convolutional neural network
  Authors: HM Keshk, XC Yin
  Year: 2021
  Citations: 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, Egypt
  Year: 2024
  Citations: 8

• Title: Classification of EgyptSat-1 images using deep learning methods
  Year: 2020
  Citations: 8

• Title: Three-pass (DInSAR) ground change detection in Sukari gold mine, Eastern Desert, Egypt
  Year: 2022
  Citations: 4

• Title: Geometric Correction of Aerial Camera and LiDAR Hybrid System Data Using GNSS/IMU
  Year: 2022
  Citations: 2

• Title: Retracted article: Sentinel-2 cloud mask classification using deep learning method
  Year: 2022
  Citations: 2

Conclusion