Asif Muzaffar | Artificial Intelligence and Machine Learning | Research Excellence Award

Dr. Asif Muzaffar | Artificial Intelligence and Machine Learning | Research Excellence Award

Teaching Fellow | Birmingham City University | United Kingdom

Dr. Asif Muzaffar is a recognized researcher in Operations and Supply Chain Management, known for advancing quantitative modelling, sustainable operations, and digital supply chain innovation. With 816 citations, 45 documents, an h-index of 16, and an i10-index of 17, his scholarly influence is reflected through publications in leading journals, including Sustainable Production and Consumption, Sustainable Development, Operations Management Research, Technological Forecasting & Social Change, International Journal of Disaster Risk Reduction, and the Journal of Services Marketing. His research portfolio encompasses 21 peer-reviewed journal papers, multiple conference contributions, and ongoing works addressing dynamic pricing, newsvendor models, sustainable procurement, and consumer behavior in digital environments. Dr. Asif Muzaffar’s contributions span supply chain contracts, institutional pressures, triple bottom line sustainability, rebate mechanisms, and technology-enabled service innovations such as AR/VR. His work often integrates simulation modelling, optimization, and game-theoretic frameworks to generate actionable insights for resilient, low-carbon, and digitally enabled supply chain systems. He has disseminated his findings at major international conferences, contributing evidence-based perspectives on biased decision-making, rebate coordination, and supply chain optimization. His research leadership extends to mentoring graduate research, shaping sustainable supply chain methodologies, and contributing as a reviewer for high-impact journals including Technological Forecasting & Social Change and Sustainable Development. Through these scholarly contributions, Dr. Asif Muzaffar has established himself as an influential voice in contemporary sustainable operations and supply chain research.

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Featured Publications

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

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.