Farzad Pashmforoush | composite materials | Best Researcher Award
Assoc. Prof. Dr. Farzad Pashmforoush , Best Researcher Award , Iran.
Dr. Farzad Pashmforoushย
ย is an Associate Professor at the University of Maragheh, specializing inย Mechanical Engineering. With a Ph.D. from Amirkabir University of Technology (2015), his expertise spansย composite materials, finite element analysis, artificial intelligence, and non-destructive testing. His research contributions, recognized withย 411 citations and an h-index of 9ย
, focus onย damage identification, numerical modeling, and advanced manufacturing techniques. Dr. Pashmforoush has authored numerousย high-impact publicationsย
ย and continues to push the boundaries ofย mechanical engineering and material sciencesย with innovative methodologies.ย ![]()
Publication Profile
Google Scholar
Orcid
Scopus
Education & Experience
ย Bachelorโs (2005-2009):ย Mechanical Engineering, University of Tabriz (Ranked 1st, 18.86 GPA)
ย Masterโs (2009-2011):ย Mechanical Engineering, Amirkabir University of Technology (Ranked 1st, 18.52 GPA)
ย Ph.D. (2011-2015):ย Mechanical Engineering, Amirkabir University of Technology (19.26 GPA)
ย Current Position:ย Associate Professor, University of Maraghehย ![]()
Suitabilty Summary
Dr. Farzad Pashmforoush, anย Associate Professor at the University of Maragheh, has made outstanding contributions to the field ofย mechanical engineering, composite materials, and non-destructive testing (NDT). Hisย pioneering research in damage characterization, artificial intelligence applications in material analysis, and advanced manufacturing techniquesย has significantly impacted the scientific community, making him a strong candidate for theย Best Researcher Award.
Professional Development
Dr. Pashmforoush is actively engaged inย cutting-edge research and academic mentoringย
. He has pioneered advancements inย composite material behavior, AI-driven structural analysis, and non-destructive evaluationย
. His research integratesย numerical simulations, experimental techniques, and machine learning algorithmsย
ย to enhance manufacturing and material testing. With extensiveย experience in FEM modeling and fracture mechanics, he collaborates with global researchers to developย robust, high-performance materialsย
. His contributions significantly impactย aerospace, automotive, and civil engineering applications, making him a distinguished figure inย mechanical and materials engineering.ย ![]()
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Research Focus
Dr. Pashmforoushโs research spans multiple domains of mechanical and material sciences
. His work on composite materials explores damage identification and characterization using advanced acoustic emission techniques
. He employs finite element modeling (FEM) for fracture mechanics simulations
and integrates artificial intelligence and deep learning
for autonomous damage recognition in composite structures. His studies also delve into non-destructive testing (NDT), optical glass finishing, and nanocomposite material analysis
. His research aims to enhance the durability, performance, and sustainability of advanced engineering materials
, bridging the gap between experimental mechanics and AI-driven simulations.
Awards & Honors
ย 1st Rankย in B.Sc. & M.Sc. Mechanical Engineering
ย Outstanding Researcher Awardย in Composite Materials & FEM
ย Best Ph.D. Dissertation Awardย on Magnetic Abrasive Finishingย ![]()
ย Numerous High-Impact Publicationsย with 400+ Citationsย ![]()
ย Recognized Reviewerย for Leading Scientific Journalsย ![]()
Publications Top Notes
ย Autonomous damage recognition in visual inspection of laminated composite structures using deep learningย โ S Fotouhi, F Pashmforoush, M Bodaghi, M Fotouhi |ย Composite Structuresย (2021) |ย
ย Cited by: 87
ย Characterization of composite materials damage under quasi-static three-point bending test using wavelet and fuzzy C-means clusteringย โ M Fotouhi, H Heidary, M Ahmadi, F Pashmforoush |ย Journal of Composite Materialsย (2012) |ย
ย Cited by: 86
ย Damage classification of sandwich composites using acoustic emission technique and k-means genetic algorithmย โ F Pashmforoush, R Khamedi, M Fotouhi, M Hajikhani, M Ahmadi |ย Journal of Nondestructive Evaluationย (2014) |ย
ย Cited by: 83
ย Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithmย โ F Pashmforoush, M Fotouhi, M Ahmadi |ย Journal of Reinforced Plastics and Compositesย (2012) |ย
ย Cited by: 72
ย Damage characterization of glass/epoxy composite under three-point bending test using acoustic emission techniqueย โ F Pashmforoush, M Fotouhi, M Ahmadi |ย Journal of Materials Engineering and Performanceย (2012) |ย
ย Cited by: 66












ย “Theoretical study on fatigue damage of sonic standing wave resonant drill-string”ย โ cited by 1 (2023).












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(2023) โ Cited by: 0