Ibrahim Aromoye | Artificial Intelligence and Machine Learning | Editorial Board Member

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Mr. Ibrahim Aromoye | Artificial Intelligence and Machine Learning | Editorial Board Member

Graduate Research Assistant | Universiti Teknologi PETRONAS | Malaysia

Mr. Ibrahim Aromoy is a promising researcher in Electrical and Electronic Engineering with a growing scholarly footprint in hybrid UAV systems, artificial intelligence, and intelligent surveillance technologies. His research is centered on the development of a Pipeline Inspection Air Buoyancy Hybrid Drone, a novel UAV concept that combines lighter-than-air and heavier-than-air technologies to improve flight endurance, stability, and inspection efficiency. By integrating deep learning–based object detection architectures into UAV platforms, his work advances real-time pipeline monitoring, anomaly identification, and autonomous decision-making for industrial applications. His contributions span AI-driven automation, robotics, swarm intelligence, energy-efficient IoT systems, and 5G-enabled surveillance technologies. He has authored several research papers in reputable international journals and conferences, including publications in IEEE Access, Neurocomputing, and Elsevier venues. These works address UAV reconnaissance, transformer-based detection models for pipeline integrity assessment, and optimization frameworks inspired by swarm behavior. His research output reflects measurable scholarly influence, with 15 Scopus citations, 7 indexed documents, and an h-index of 2. Mr. Ibrahim Aromoy has participated in multiple research and development projects, contributing to UAV design, embedded hardware integration, machine learning pipelines, and cyber-secure control systems. His work in hybrid drone architecture and automated surveillance has been supported by competitive institutional funding, reinforcing the technological relevance and innovation potential of his research. His scientific contributions extend beyond publications to academic service. He serves as a peer reviewer for high-impact journals such as IEEE Access and Results in Engineering, supporting the advancement of rigorous research dissemination in engineering and applied sciences. His expertise also includes AI vision systems, OpenCV-based automation, and embedded cybersecurity applications for unmanned systems, further strengthening his interdisciplinary research profile. Mr. Ibrahim Aromoy has been recognized with research-focused scholarships and academic distinctions that support his ongoing work in UAV innovation and intelligent automation. Through his integrated expertise in UAV engineering, deep learning, and intelligent inspection systems, he continues to contribute meaningfully to the evolution of smart surveillance, autonomous robotics, and AI-augmented engineering technologies.

Profiles: Scopus | ORCID | Google Scholar | ResearchGate | Web of Science

Featured Publications

1. Aromoye, I., Lo, H., Sebastian, P., Ghulam, E., & Ayinla, S. (2025). Significant advancements in UAV technology for reliable oil and gas pipeline monitoring. Computer Modeling in Engineering & Sciences, 142(2), 1155.

2. Aromoye, I. A., Hiung, L. H., & Sebastian, P. (2025). P-DETR: A transformer-based algorithm for pipeline structure detection. Results in Engineering, 26, 104652.

3. Zahid, F., Ali, S. S. A., & Aromoye, I. A. (2025). Exploring the potential benefits and overcoming the constraints of virtual and augmented reality in operator training. Transportation Research Procedia, 84, 625–632.

4. Mansoor, Y., Zahid, F., Azhar, S. S., Rajput, S., & Aromoye, I. A. (2025). Energy-efficient solar water pumping: The role of PLCs and DC-DC boost converters in addressing water scarcity. Transportation Research Procedia, 84, 681–688.

5. Zahid, F., Rajput, S., Ali, S. S. A., & Aromoye, I. A. (2025). Challenges and innovations in 3D object recognition: The integration of LiDAR and camera sensors for autonomous applications. Transportation Research Procedia, 84, 618–624.

Amir R. Masoodi | Artificial Intelligence and Machine Learning | Editorial Board Member

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Assist. Prof. Dr. Amir R. Masoodi | Artificial Intelligence and Machine Learning | Editorial Board Member

Assistant Professor | Ferdowsi University of Mashhad | Iran

Assist. Prof. Dr. Amir R. Masoodi is a highly accomplished structural engineering researcher whose work spans nonlinear mechanics, composite structures, vibration analysis, finite element modeling, and advanced material systems. With 1,789 Scopus citations, 77 publications, and an h-index of 29, he has established a strong international research footprint in computational mechanics, structural stability, soil–structure interaction, wave propagation, and multiscale modeling of advanced composites. His research contributions include developing novel finite element formulations for beams, plates, and shells, particularly for functionally graded materials (FGMs), carbon nanotube (CNT)-reinforced composites, graphene nanocomposites, and porous structural systems. Assist. Prof. Dr. Amir R. Masoodi’s work on nonlinear dynamic analysis, thermal–mechanical coupling, shell instability, and multiscale behavior of nano-engineered materials has been widely cited and influential in advancing modern structural design methodologies. He has published extensively in leading journals such as Composite Structures, Engineering Structures, Mechanics of Advanced Materials and Structures, Aerospace Science and Technology, Scientific Reports, and Applied Sciences. His publications address cutting-edge topics including vibration of hybrid nano-reinforced shells, multiscale characterization of nanocomposites, nonlinear buckling behavior of tapered beams, thermomechanical modeling of composite cables, and smart materials incorporating shape-memory alloys. Assist. Prof. Dr. Amir R. Masoodi has presented his findings at numerous international conferences and contributed several book chapters, including work on nanofillers and thermal properties in advanced materials. His research output extends to R&D projects, predictive modeling, and computational innovations in structural and nano-engineered systems. He has been recognized with multiple distinguished researcher awards, national elite recognitions, and research excellence honors. His expertise is further reflected in his editorial board memberships and contributions as a reviewer for reputable journals. Overall, Assist. Prof. Dr. Amir R. Masoodi’s research stands at the intersection of computational mechanics, smart materials, and multiscale structural engineering, offering impactful advances for next-generation civil, mechanical, and aerospace systems.

Profiles: Scopus | ORCID | Google Scholar | Sci Profiles | Web of Science

Featured Publications

1. Sobhani, E., Masoodi, A. R., & Ahmadi-Pari, A. (2021). Vibration of FG-CNT and FG-GNP sandwich composite coupled conical–cylindrical–conical shell. Composite Structures, 273, 114281.

2. Sobhani, E., Masoodi, A. R., Civalek, O., & Ahmadi-Pari, A. R. (2021). Agglomerated impact of CNT vs. GNP nanofillers on hybridization of polymer matrix for vibration of coupled hemispherical–conical–conical shells. Aerospace Science and Technology, 120, 107257.

3. Rezaiee-Pajand, M., Sobhani, E., & Masoodi, A. R. (2020). Free vibration analysis of functionally graded hybrid matrix/fiber nanocomposite conical shells using multiscale method. Aerospace Science and Technology, 105, 105998.

4. Rezaiee-Pajand, M., Arabi, E., & Masoodi, A. R. (2019). Nonlinear analysis of FG-sandwich plates and shells. Aerospace Science and Technology, 87, 178–189.

5. Rezaiee-Pajand, M., Masoodi, A. R., & Mokhtari, M. (2018). Static analysis of functionally graded non-prismatic sandwich beams. Advances in Computational Design, 3(2), 165–190.