Assoc. Prof. Dr. Farzad Pashmforoush , Best Researcher Award , Iran.
Dr. Farzad Pashmforoush 
is an Associate Professor at the University of Maragheh, specializing in Mechanical Engineering. With a Ph.D. from Amirkabir University of Technology (2015), his expertise spans composite materials, finite element analysis, artificial intelligence, and non-destructive testing. His research contributions, recognized with 411 citations and an h-index of 9 
, focus on damage identification, numerical modeling, and advanced manufacturing techniques. Dr. Pashmforoush has authored numerous high-impact publications 
and continues to push the boundaries of mechanical engineering and material sciences with innovative methodologies. 
Publication Profile
Education & Experience
Bachelor’s (2005-2009): Mechanical Engineering, University of Tabriz (Ranked 1st, 18.86 GPA)
Master’s (2009-2011): Mechanical Engineering, Amirkabir University of Technology (Ranked 1st, 18.52 GPA)
Ph.D. (2011-2015): Mechanical Engineering, Amirkabir University of Technology (19.26 GPA)
Current Position: Associate Professor, University of Maragheh 
Suitabilty Summary
Dr. Farzad Pashmforoush, an Associate Professor at the University of Maragheh, has made outstanding contributions to the field of mechanical engineering, composite materials, and non-destructive testing (NDT). His pioneering research in damage characterization, artificial intelligence applications in material analysis, and advanced manufacturing techniques has significantly impacted the scientific community, making him a strong candidate for the Best Researcher Award.
Professional Development
Dr. Pashmforoush is actively engaged in cutting-edge research and academic mentoring 
. He has pioneered advancements in composite material behavior, AI-driven structural analysis, and non-destructive evaluation 
. His research integrates numerical simulations, experimental techniques, and machine learning algorithms 
to enhance manufacturing and material testing. With extensive experience in FEM modeling and fracture mechanics, he collaborates with global researchers to develop robust, high-performance materials 
. His contributions significantly impact aerospace, automotive, and civil engineering applications, making him a distinguished figure in mechanical and materials engineering. 
Research Focus
Dr. Pashmforoush’s 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
1st Rank in B.Sc. & M.Sc. Mechanical Engineering
Outstanding Researcher Award in Composite Materials & FEM
Best Ph.D. Dissertation Award on Magnetic Abrasive Finishing 
Numerous High-Impact Publications with 400+ Citations
Recognized Reviewer for Leading Scientific Journals 
Publications Top Notes
Autonomous damage recognition in visual inspection of laminated composite structures using deep learning – S Fotouhi, F Pashmforoush, M Bodaghi, M Fotouhi | Composite Structures (2021) | 
Cited by: 87
Characterization of composite materials damage under quasi-static three-point bending test using wavelet and fuzzy C-means clustering – M Fotouhi, H Heidary, M Ahmadi, F Pashmforoush | Journal of Composite Materials (2012) | Cited by: 86
Damage classification of sandwich composites using acoustic emission technique and k-means genetic algorithm – F Pashmforoush, R Khamedi, M Fotouhi, M Hajikhani, M Ahmadi | Journal of Nondestructive Evaluation (2014) | Cited by: 83
Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithm – F Pashmforoush, M Fotouhi, M Ahmadi | Journal of Reinforced Plastics and Composites (2012) | Cited by: 72
Damage characterization of glass/epoxy composite under three-point bending test using acoustic emission technique – F Pashmforoush, M Fotouhi, M Ahmadi | Journal of Materials Engineering and Performance (2012) | Cited by: 66