Farzad Pashmforoush | composite materials | Best Researcher Award

Farzad Pashmforoush | composite materials | Best Researcher Award

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

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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

Mr. Kaan Nuhoglu | 3D printing of composites Awards | Best Researcher Award

Mr. Kaan Nuhoglu | 3D printing of composites Awards | Best Researcher Award

Mr. Kaan Nuhoglu , University of Miami , United States

Kaan Nuhoğlu is a dedicated mechanical engineer pursuing his Ph.D. at the University of Miami, where he specializes in the analysis and optimization of composite materials and adhesive joints. Born on August 19, 1995, Kaan is multilingual, fluent in English, German, and Spanish. His academic journey began at Ege University in İzmir, Turkey, where he earned his bachelor’s degree in mechanical engineering, followed by a master’s degree from Izmir Institute of Technology. Kaan is proficient in various technical tools such as Solidworks, AutoCAD, ANSYS, Moldex3D, Matlab, and CatiV5, and has contributed significantly to his field through several publications in high-impact journals. His research focuses on improving the mechanical behavior of composite structures, evidenced by his recent work on laser-treated composites and the use of nanofibers in adhesive joints. Kaan combines his technical skills with a passion for continuous personal and professional growth, aiming to advance his expertise daily​

Professional Profile:

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🎓 Education

  • Mechanical Engineering BSc
    Ege University, İzmir, Turkey
  • Mechanical Engineering MSc
    Izmir Institute of Technology, İzmir, Turkey
  • Mechanical Engineering Ph.D.
    University of Miami, Miami, USA

🛠️ Computer Skills

  • Solidworks: 2D, 3D CAD Modeling
  • AutoCAD: 2D Design
  • ANSYS: FEA
  • Moldex3D: Molding Simulation and Analysis
  • Matlab: Numerical Computing
  • CatiV5: 3D CAD Modeling
  • Microsoft Office

🌐 Language Skills

  • English
  • German
  • Spanish
Publication Top Notes: