Mohamed Abdelkader | AI-Based Robot Perception | Research Excellence Award

Published on by Robotics and Automation

Research Excellence Award

Mohamed Abdelkader
Prince Sultan University

Mohamed Abdelkader
Affiliation Prince Sultan University
Country Saudi Arabia
Scopus ID 57197062034
Documents 35
Citations 575
h-index 11
Subject Area AI-Based Robot Perception
Event International Robotics and Automation Awards
ORCID 0000-0002-0518-852X

Mohamed Abdelkader, affiliated with Prince Sultan University, is a researcher whose work focuses on AI-based robot perception, autonomous systems, computer vision, and intelligent robotic navigation. His scholarly contributions demonstrate the integration of artificial intelligence with robotic sensing technologies to improve perception, localization, and autonomous decision-making. His research output has attracted significant academic attention through publications indexed in Scopus and citations across robotics and artificial intelligence literature.[1]

Abstract

Mohamed Abdelkader has established an active research profile in AI-based robot perception through investigations involving autonomous navigation, computer vision, robotic sensing, and intelligent decision-making. His publications contribute to improving robotic awareness of dynamic environments by integrating perception algorithms with artificial intelligence techniques. These studies support advancements in autonomous systems capable of operating safely and efficiently across diverse applications. His scholarly productivity, citation record, and interdisciplinary collaborations demonstrate sustained contributions to robotics research while promoting practical innovation, scientific dissemination, and continued academic development within intelligent robotic technologies.[1][2]

Keywords

AI-Based Robot Perception, Computer Vision, Autonomous Robotics, Robotic Navigation, Machine Learning, Artificial Intelligence, Intelligent Systems, Mobile Robots, Sensor Fusion, Autonomous Vehicles.

Introduction

Artificial intelligence has significantly transformed robotic perception by enabling machines to interpret complex environments through visual and sensor-based information. Mohamed Abdelkader’s research reflects these developments by investigating perception frameworks that improve robotic autonomy, environmental understanding, and adaptive navigation while supporting reliable performance across intelligent robotic applications.[2]

Research Profile

Working at Prince Sultan University, Mohamed Abdelkader has developed a research portfolio centered on autonomous robotics, perception systems, and artificial intelligence. His publications emphasize practical solutions that combine computer vision, localization, mapping, and machine learning techniques to enhance robotic awareness and decision-making in real-world environments while encouraging interdisciplinary collaboration.[1]

Research Contributions

His research contributions include improving robotic perception algorithms, integrating intelligent sensing technologies, and advancing autonomous navigation capabilities. These studies support greater operational efficiency for robotic platforms while expanding the application of artificial intelligence in perception-driven systems used across industrial, academic, and emerging autonomous environments.[3]

Publications

The researcher’s publication record includes peer-reviewed articles addressing robot perception, intelligent navigation, machine learning, and computer vision. These publications have contributed to the growing body of literature in robotics by presenting methodologies that improve environmental understanding and autonomous performance while maintaining scientific rigor and reproducibility.[2]

Research Impact

With 35 indexed publications, 575 citations, and an h-index of 11, Mohamed Abdelkader has achieved measurable scholarly visibility within robotics and artificial intelligence research. These metrics indicate continued academic engagement and demonstrate that his research findings have influenced related investigations in autonomous robotic perception and intelligent systems.[1]

Award Suitability

The Research Excellence Award recognizes researchers who demonstrate sustained scholarly productivity, impactful publications, and meaningful scientific contributions. Mohamed Abdelkader’s achievements in AI-based robot perception, supported by recognized research metrics and interdisciplinary innovation, align with the objectives of honoring excellence in robotics and automation research.[4]

Conclusion

Mohamed Abdelkader’s research reflects consistent advancement in AI-driven robotic perception through scientifically validated investigations and collaborative innovation. His academic record demonstrates meaningful contributions to autonomous robotics while supporting future developments in intelligent perception technologies and practical robotic applications across multiple research domains.[1][4]

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Mohamed Abdelkader, Author ID 57197062034. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57197062034
  2. Google Scholar. (n.d.). Scholar profile of Mohamed Abdelkader.
    https://scholar.google.com/citations?user=hk5GW30AAAAJ&hl=en&oi=sra
  3. MDPI. (2022). OCTUNE: Optimal Control Tuning Using Real-Time Data with Algorithm and Experimental Results.
    https://doi.org/10.3390/s22239240
  4. International Robotics and Automation Awards. (2026). Research Excellence Award.
    https://roboticsandautomation.org/

Mr. Getachew Getu Enyew | Artificial Intelligence | Research Excellence Award

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Mr. Getachew Getu Enyew | Artificial Intelligence | Research Excellence Award

Addis Ababa Science and Technology University | Ethiopia

Mr. Getachew Getu Enyew is an academic researcher and AI/ML engineer specializing in AI-driven cybersecurity, intelligent autonomous systems, and robotic perception. A fast-track MSc graduate in Computer Engineering from Addis Ababa Science and Technology University, he has developed machine learning models for threat detection, Artificial Intelligence, anomaly analysis, and decision-making systems applied to critical infrastructure. He currently works as an AI/ML Engineer and Application Software Developer in national information network security projects while also serving as a lecturer and research supervisor. His research interests focus on trustworthy AI, intelligent robotics, and scalable cybersecurity solutions for autonomous and cloud-based systems.

 

Citation Metrics (Google Scholar)

3
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Dr. Peter Williams | Safe Human-Robot Collaboration | Research Excellence Award

Published on by Robotics and Automation

Dr. Peter Williams | Safe Human-Robot Collaboration | Research Excellence Award

University of Hull | United Kingdom

Dr. Peter Williams is an independent researcher and retired Senior Lecturer in Technology Enhanced Learning at the University of Hull, United Kingdom, where he served until 2020. He was an early pioneer in the design and management of online courses and blended learning, particularly for small businesses, and later led staff development initiatives in blended learning and ICT. He designed and directed degree programs in educational technology and is recognized as a University Teaching Fellow and a Senior Fellow of the Higher Education Academy, UK. Dr. Williams successfully co-supervised eight doctoral students researching the application of new technologies in learning, teaching, and assessment, and has served as an external examiner for PhD awards. His doctoral research examined management issues in e-learning within universities, later specializing in the impact of emerging technologies on assessment in higher education. His single-authored publications address knowledge development in higher education, graduate competencies, learning analytics, blockchain-based micro-credentials, artificial intelligence, hybrid intelligence, and human-agentic AI systems for learning and assessment. He has supported digital education at the University of Leeds, served as an external examiner at the University of Malta, peer-reviewed over 30 journal articles, Safe Human-Robot Collaboration and currently serves on the editorial boards of Education Sciences and Artificial Intelligence and Education.

 

Citation Metrics (Scopus)

400
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359

Documents
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Featured Publications


Does Competency-Based Education with Blockchain Signal a New Mission for Universities?

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Prof. Hsin-Yuan Chen | Smart Robot | Best Researcher Award

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Prof. Hsin-Yuan Chen | Smart Robot | Best Researcher Award

Zhejiang University | China

Prof.  Hsin-Yuan  Chen is a distinguished Chang Jiang Scholar Professor and director at the center of digital technology entrepreneurship and innovation, Zhejiang University, China, and serves as an adjunct distinguished professor at Patil University, India. She holds a Ph.d. in aerospace engineering from national Cheng Kung university, where she also earned her bachelor’s degree through a direct Ph.d. program. With extensive academic and industrial experience, Dr. Chen has held key positions including professor and dean at Fujian normal university, and ai chief technology officer at Geosat technology and mobiletron electronics. her expertise spans artificial intelligence, robotics, big data, cloud computing, Smart Robot and digital innovation. She has authored 78 scholarly documents, which have collectively received 1,761 citations from 1,556 sources, achieving an h-index of 27, reflecting her significant academic impact. her exceptional contributions have been recognized globally through prestigious honors such as the IET fellowship, Asean fellowship, global top engineers medal, and multiple international awards in ai, cloud technology, and robotics. a respected editor and reviewer for numerous international journals, Dr. Chen continues to advance interdisciplinary innovation in digital transformation, artificial intelligence, and emerging technologies worldwide.

Profiles: Scopus | Orcid | Google Scholar

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Sharma, C., Chanana, N., & Chen, H.-Y. (2025, June). Mapping the evolution: A bibliometric analysis of employee engagement and performance in the age of artificial intelligence-based solutions. Information, 16(7), 555.

Chen, H.-Y., Sharma, K., Sharma, C., & Sharma, S. (2024, November 9). Advancements in handwritten Devanagari character recognition: A study on transfer learning and VGG16 algorithm. Discover Applied Sciences. Springer Nature.

Chen, H.-Y. (2023). Artificial intelligence robots and fuzzy logic – Robotics – AI – ICT. Scientific Journal Impact Factor.

Chen, H.-Y. (2023). Blockchain and cryptocurrency: A bibliometric analysis. Journal of Advanced Computational Intelligence and Intelligent Informatics, 27(6), 822–832.

Chiang, Y.-F., Lin, I.-C., Huang, K.-C., Chen, H.-Y., Ali, M., Huang, Y.-J., & Hsia, S.-M. (2023). Caffeic acid’s role in mitigating polycystic ovary syndrome by countering apoptosis and ER stress triggered by oxidative stress. Biomedicine & Pharmacotherapy, 166, 115327.

Assoc. Prof. Dr. Gokhan Guven | Robotics | Best Researcher Award

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Assoc. Prof. Dr. Gokhan Guven | Robotics | Best Researcher Award

Mugla Sitki Kocman University | Turkey

Dr. Gokhan Guven is a Ph.D. Candidate in the department of curriculum and instruction at Mugla Sitki Kocman University, turkey, specializing in science education under the supervision of dr. yusuf sulun. he earned his bachelor’s degree in elementary science education from pamukkale university and completed his master’s in science education at mugla sitki kocman university, where his thesis focused on preservice elementary teachers’ reflection journal writing and epistemological beliefs in science and technology laboratory applications. Currently pursuing his doctoral studies in science education, dr. guven’s research interests include energy education, science teacher education, and science laboratory applications. throughout his academic career, he has served as a teaching assistant in various laboratory-based courses, including general biology, general physics, Robotics and general chemistry, contributing significantly to hands-on science instruction and pedagogy. his scholarly contributions have garnered 179 citations across 12 documents, with an h-index of 7, reflecting the impact and recognition of his research within the scientific and educational community. fluent in both english and turkish, Dr. guven continues to advance his research and academic pursuits, focusing on enhancing the quality and effectiveness of science education at both theoretical and practical levels.

Profiles: Scopus | Orcid

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Güven, G., Orhan Özen, S., & Şarlakkaya, K. (2025). Virtual reality applications integrated into the 5E learning model in environmental topics in science education. Research in Science & Technological Education. Advance online publication.

Kozcu Cakir, N., & Guven, G. (2025). Enhancing engineering design, scientific creativity, and decision-making skills in prospective science teachers through engineering design-based robotics coding applications. Research in Science & Technological Education. Advance online publication.

Güven, G., & ÖzüneL, Y. (2023). Arduino destekli robotik kodlama etkinlikleri ile ilkokul 2. sınıf doğal afetler konusunun öğretimi. Ege Bilimsel Araştırmalar Dergisi.

Güven, G., & Göçen Kabaran, G. (2023). Yenilenebilir enerji eğitimine yönelik bir öğretim tasarımı geliştirme ve değerlendirme. Eğitim Teknolojisi Kuram ve Uygulama.

Guven, G., Kozcu Cakir, N., Sulun, Y., Cetin, G., & Guven, E. (2022). Arduino-assisted robotics coding applications integrated into the 5E learning model in science teaching. Journal of Research on Technology in Education, 54(1), 1–20.