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Dr. Nadeem Fareed Over the past two decades, Light Detection and Ranging (LiDAR) has evolved from early NASA-led airborne laser altimetry into a mature and widely adopted technology for vegetation remote sensing. Advances in laser engineering, signal processing, IMU/GNSS integration, and carrier platforms such as UAS, MLS, and SLAM systems have enabled multiscale observations of vegetation structure and dynamics. This review synthesizes developments in ALS discrete-return and full-waveform systems, photon-counting, multispectral, and hyperspectral LiDAR, alongside modern data fusion and AI-driven processing approaches. The body of work comprises 11 documents, receiving 138 citations from 135 publications, with an h-index of 7.
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Assoc. Prof. Dr. Wubin Shan is a researcher whose work focuses on energy-absorbing materials and structures, micro/nano 3D and 4D printing, nonlinear system dynamics, flexible electronics, and mechatronic equipment design with mechanical analysis. His research combines advanced manufacturing and multidisciplinary engineering approaches to solve complex technical challenges. He has led several competitive research projects and published 18 scholarly documents, achieving 411 citations from 407 citing documents with an h-index of 7. In addition, he holds numerous authorized invention patents and actively contributes to academic service and student mentorship, with teams receiving recognition in national and provincial engineering, innovation, and entrepreneurship competitions.
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Assist. Prof. Dr. Sameh Attia-Essaies is an Assistant Professor and researcher specializing in inorganic chemistry, composite materials, and clay mineral science. He holds a PhD in Inorganic Chemistry with excellent distinction and possesses strong expertise in structural, thermal, mechanical, and physicochemical characterization techniques, including X-ray diffraction, FT-IR spectroscopy, and thermal analysis. His research interests focus on mineral systems, composite materials, brines, phase diagram studies, and organic synthesis. His scholarly contributions include 10 scientific documents, receiving 100 citations across 90 citing documents, with an h-index of 5, demonstrating consistent research impact.
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Dr. Suraj Yadav is a researcher specializing in radar remote sensing, precision agriculture, and AI-driven geospatial analytics. His work integrates UAV-based multispectral, hyperspectral, LiDAR, and microwave sensing with physics-informed modeling and deep learning to enable robust crop monitoring, nitrogen estimation, and yield prediction. He has led the calibration and validation of advanced imaging spectroscopy platforms across diverse crop types and land surface conditions. His scholarly contributions include 21 research documents, receiving 173 citations across 141 citing publications, with an h-index of 6, reflecting sustained research impact.
Mrs. Hanane ABBOU is a PhD Candidate and Research Assistant in Medical Biotechnology at Mohammed VI University of Sciences and Health and the Mohammed VI Center for Research and Innovation. Her research focuses on computational investigations of cannabinoid-based therapeutics targeting the endocannabinoid system, with emphasis on Cannabis and Moroccan genetic diversity. She holds an MSc in Medical Biotechnology and has professional experience in pharmacovigilance and scientific publishing. Her scholarly profile reflects 14 citations by 13 documents, 7 published documents, and an h-index of 2, with the h-index view disabled in preview mode, highlighting her growing research impact in computational pharmacology.
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Assist. Prof. Dr. Manea Mohammed Saleh Almatared is an Assistant Professor in the Civil Engineering Department at the Engineering School, Najran University, specializing in the application of advanced technologies in infrastructure, construction, and facility management. He holds a Ph.D. and M.Sc. in Civil Engineering from Western Michigan University, USA, and a B.Sc. in Civil Engineering from Najran University, KSA. His research interests encompass Digital Twin technologies in construction and infrastructure, Building Information Modeling (BIM), real-time virtual and physical data integration, and predictive maintenance driven by the Internet of Things (IoT) and Artificial Intelligence (AI). Dr. Almatared has produced impactful scientific contributions with 121 citations from 117 citing documents, 4 published documents, and an h-index of 4, reflecting the academic strength and relevance of his work. His research aims to improve efficiency, sustainability, and safety in built environments through the adoption of cutting-edge digital solutions in civil engineering. Alongside his research, he has contributed to academic and administrative roles, including involvement in scientific research committees, accreditation and quality teams, student development, and community engagement. With both academic and practical experience—enhanced by his work as Assistant Project Manager and Research Assistant at Western Michigan University—Dr. Almatared remains dedicated to academic excellence, technological innovation, and preparing the next generation of civil engineers to meet future industry challenges.
Hakimi, O., Liu, H., Abudayyeh, O., Houshyar, A., Almatared, M., & Alhawiti, A. (2023). Data fusion for smart civil infrastructure management: A conceptual digital twin framework. Buildings, 13(11), 2725.
Almatared, M., Liu, H., Abudayyeh, O., Hakim, O., & Sulaiman, M. (2023). Digital-twin-based fire safety management framework for smart buildings. Buildings, 14(1), 4.
Almatared, M., Liu, H., Tang, S., Sulaiman, M., Lei, Z., & Li, H. X. (2022). Digital twin in the architecture, engineering, and construction industry: A bibliometric review. Construction Research Congress 2022, 670–678.
Tang, S., Liu, H., Almatared, M., Abudayyeh, O., Lei, Z., & Fong, A. (2022). Towards automated construction quantity take-off: An integrated approach to information extraction from work descriptions. Buildings, 12(3), 354.
Almatared, M. (2024). An integrated digital twin framework and evacuation simulation system for enhanced safety in smart buildings. Doctoral dissertation, Western Michigan University.
Dr. Partha Ghosh is a seasoned academic and researcher with more than 22 years of professional experience in Computer Science and Information Technology, currently serving as Associate Professor in the Department of Information Technology and Head of the Department of Computer Science and Business Systems at Netaji Subhash Engineering College, Kolkata. His research expertise spans Computer Networking, Machine Learning, Cloud Computing, Intrusion Detection Systems, Optimization Algorithms, Feature Selection and Classification Techniques, with a focus on developing secure, intelligent and high-performance cloud-based computational environments. His scholarly impact is reflected through 16 SCOPUS-indexed documents, 194 citations by 173 documents and an h-index of 7. Additionally, his ORCID profile lists 20 research works, and according to Google Scholar he has 333 citations (244 since 2020), an h-index of 10 (9 since 2020) and an i10-index of 10 (9 since 2020), demonstrating consistent and growing research visibility. To date, he has authored 24 publications including indexed journal papers, international conference papers and book chapters. He has taught a wide range of core and advanced courses such as Computer Organisation, Computer Networks, Advanced Computer Networking, Microprocessors and Microcontrollers and Database Management Systems at undergraduate and postgraduate levels. His academic engagement also includes serving as Editor-in-Chief and Editorial Board Member of reputed journals and holding multiple Fellow and Life Membership roles across professional bodies, underscoring his continued commitment to research innovation, knowledge dissemination and academic leadership.
Ghosh, P., Mandal, A. K., & Kumar, R. (2015). An efficient cloud network intrusion detection system. In Information Systems Design and Intelligent Applications: Proceedings of …
Ghosh, P., Karmakar, A., Sharma, J., & Phadikar, S. (2018). CS-PSO based intrusion detection system in cloud environment. In Emerging Technologies in Data Mining and Information Security: Proceedings …
Ghosh, P., & Mitra, R. (2015). Proposed GA-BFSS and logistic regression based intrusion detection system. In Proceedings of the 2015 Third International Conference on Computer …
Ghosh, P., Sarkar, D., Sharma, J., & Phadikar, S. (2021). An intrusion detection system using modified-firefly algorithm in cloud environment. International Journal of Digital Crime and Forensics, 13(2), 77–93.
Ghosh, P., Debnath, C., Metia, D., & Dutta, R. (2015). An efficient hybrid multilevel intrusion detection system in cloud environment. IOSR Journal of Computer Engineering, 16(4), 16–26.
Ghosh, P., Shakti, S., & Phadikar, S. (2016). A cloud intrusion detection system using novel PRFCM clustering and KNN based dempster-shafer rule. International Journal of Cloud Applications and Computing, 6(4), 18–35.