Mehdi Mohajeri | Engineering | Best Researcher Award

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Dr. Mehdi Mohajeri | Engineering | Best Researcher Award

Ph.D. Graduate at Amirkabir Univ. of Technology (Tehran Polytechnic), Iran

Mehdi Mohajeri is a Ph.D. candidate in Construction Management and Engineering at Amirkabir University of Technology, Tehran, Iran. His research focuses on construction safety, risk assessment, and the application of advanced decision-making techniques to improve safety culture and reduce hazards in high-rise construction projects. With a strong academic foundation and multiple published works, he has contributed to the development of methodologies such as fuzzy multi-criteria decision-making (FMCDM), Bayesian networks, and fuzzy failure mode and effect analysis (FFMEA). Mehdi also serves as a Graduate Teaching Assistant, demonstrating his commitment to both research and education. His work plays a crucial role in enhancing safety practices in the construction industry, and he continues to explore new solutions to address challenges in the field.

Professional Profile

Education

Mehdi Mohajeri holds a Bachelor’s degree in Civil Engineering from Islamic Azad University Kerman Branch (2003-2007). He pursued a Master’s degree in Civil Engineering with a specialization in HSE (Health, Safety, and Environmental) Engineering at Amirkabir University of Technology, Tehran, Iran, completing it in 2013. Currently, he is working toward his Ph.D. in Construction Management and Engineering at Amirkabir University of Technology, where he has been researching under the supervision of Dr. Abdollah Ardeshir since 2016. His doctoral studies focus on improving safety measures and assessing risks in the construction industry using innovative decision-making methods, further building upon his educational background in civil engineering and safety management.

Professional Experience

Mehdi Mohajeri has been a Graduate Teaching Assistant at Amirkabir University of Technology since 2018, where he supports students in construction management courses and contributes to the academic environment. His teaching role reflects his passion for both research and knowledge sharing. In his research career, Mehdi has published multiple influential journal articles related to safety culture, risk assessment, and decision-making models in construction. He has collaborated with experts to analyze construction safety risks using methods like AHP-DEA and FFMEA. His work has been published in well-regarded journals, contributing valuable insights to the field of construction safety. Additionally, Mehdi is actively involved in preparing manuscripts for publication, exploring causality patterns in safety-related incidents and the influence of safety supervisors on construction workers’ behavior.

Research Interests

Mehdi Mohajeri’s primary research interests lie in construction safety, risk assessment, and the application of advanced decision-making models in the construction industry. He focuses on improving safety culture and reducing hazards, particularly in high-rise construction projects, using innovative approaches like fuzzy multi-criteria decision-making (FMCDM), Fuzzy Failure Mode and Effect Analysis (FFMEA), and Bayesian networks. Mehdi is also exploring causality patterns of safety-related incidents in construction, with a keen interest in understanding the influence of safety supervisors on workers’ cognitive behavior and safety performance. His work aims to enhance safety management practices and ensure the well-being of workers in high-risk construction environments, contributing to the broader field of civil engineering and construction management.

Awards and Honors

Although Mehdi Mohajeri’s CV does not list specific awards and honors, his academic and professional achievements, including multiple published journal articles in high-impact journals, reflect his excellence in research. His recognition comes through his impactful work in safety management within the construction industry. He has been involved in several prestigious projects and collaborations with experts in the field, contributing to safety advancements. Additionally, his role as a Graduate Teaching Assistant highlights his commitment to education and his recognition as a skilled and knowledgeable individual in his field. The focus of his work continues to be acknowledged by the academic and professional community, further cementing his reputation as a leading researcher in construction safety and risk management.

Publications Top Noted

  • Title: Assessment of safety culture among job positions in high-rise construction: a hybrid fuzzy multi criteria decision-making (FMCDM) approach
    Authors: A. Ardeshir, M. Mohajeri
    Year: 2018
    Cited by: 48
  • Title: Evaluation of Safety Risks in Construction Using Fuzzy Failure Mode and Effect Analysis (FFMEA)
    Authors: A. Ardeshir, M. Mohajeri, M. Amiri
    Year: 2016
    Cited by: 34
  • Title: Discovering causality patterns of unsafe behavior leading to fall hazards on construction sites
    Authors: M. Mohajeri, A. Ardeshir, M.T. Banki, H. Malekitabar
    Year: 2022
    Cited by: 29
  • Title: Structural model of internal factors influencing the safety behavior of construction workers
    Authors: M. Mohajeri, A. Ardeshir, H. Malekitabar, S. Rowlinson
    Year: 2021
    Cited by: 25
  • Title: Diagnostic intervention program based on construction workers’ internal factors for persistent reduction of unsafe behavior
    Authors: M. Mohajeri, A. Ardeshir, H. Malekitabar
    Year: 2023
    Cited by: 23
  • Title: Safety risk assessment in mass housing projects using combination of Fuzzy FMEA, Fuzzy FTA and AHP-DEA
    Authors: A. Ardeshir, M. Amiri, M. Mohajeri
    Year: 2013
    Cited by: 14
  • Title: Analysis of Construction Safety Risks Using AHP-DEA Integrated Method
    Authors: M. Mohajeri, A. Ardeshir
    Year: 2016
    Cited by: 11
  • Title: Ranking main causes of falling from height hazard in high-rise construction projects
    Authors: M. Mohajeri, M. Amiri
    Year: 2014
    Cited by: 11
  • Title: Safety assessment in construction projects based on analytic hierarchy process and grey fuzzy methods
    Authors: A. Ardeshir, M. Mohajeri, M. Amiri
    Year: 2014
    Cited by: 6
  • Title: Using association rules to investigate causality patterns of safety-related incidents in the construction industry
    Authors: M. Mohajeri, A. Ardeshir, M.T. Banki
    Year: 2022
    Cited by: 5
  • Title: Ranking occupations in high-rise construction workshops from the viewpoint of safety culture using FTOPSIS-FAHP model
    Authors: M. Amiri, M. Mohajeri
    Year: 2017
    Cited by: Not available

Xu Zhang | Engineering Award | Best Scholar Award

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Dr. Xu Zhang | Engineering Award | Best Scholar Award

Associate professor at Hubei University of Technology, China

Xu Zhang is a distinguished scholar specializing in intelligent non-destructive testing (NDT) technologies. With a solid academic foundation in Acoustics, her expertise spans sensor design, guided wave testing, and the integration of artificial intelligence in NDT systems. Zhang has been the principal investigator on several prestigious projects, including National Natural Science Foundation of China and National Key Research and Development Plan projects. She has made significant contributions to the fields of electromagnetic acoustic transducers (EMATs), guided wave detection methods, and corrosion imaging. Her research is not only innovative but also highly relevant to critical industries such as aerospace, automotive, and infrastructure.

Professional Profile

Education

Xu Zhang’s academic journey began with a Bachelor’s degree in Acoustics from Nanjing University in 2010. She furthered her education with a Master’s and PhD in Acoustics from the prestigious Chinese Academy of Sciences, where she honed her research focus on non-destructive testing technologies. In 2016, she became an Associate Professor in the Department of Mechanical Engineering at Hubei University of Technology. Xu is currently a Visiting Fellow at the University of Bristol, where she collaborates with global experts on advanced NDT methods. Her academic background has equipped her with a deep understanding of the complexities in material testing, structural health monitoring, and the application of electromagnetic and ultrasonic technologies in engineering.

Experience

Xu Zhang has extensive experience in the field of non-destructive testing and advanced materials inspection. Since 2016, she has served as an Associate Professor at Hubei University of Technology, specializing in intelligent NDT technologies. Zhang has been the Principal Investigator (PI) in numerous high-profile national and provincial projects, focusing on ultrasonic and electromagnetic testing techniques for stress corrosion cracking and high-temperature creep materials. Notable projects she has led include the development of an ultrasonic phased array detection system for automotive steering parts and the creation of technology for pipeline corrosion imaging. Her expertise spans sensor design, guided wave testing, and the integration of artificial intelligence into NDT systems. Zhang is also a Senior Member of the Chinese Mechanical Engineering Society and an active participant in global research discussions on intelligent testing methodologies.

Research Focus

Xu Zhang’s research is primarily focused on intelligent non-destructive testing (NDT) technologies, with a specific emphasis on ultrasonic and electromagnetic guided wave techniques. She is dedicated to the development of advanced sensor systems and diagnostic tools that can detect flaws and assess material integrity in complex engineering structures. One of her key areas of research is the integration of artificial intelligence into NDT methodologies, enabling more efficient and accurate defect detection. Zhang’s work has applications in diverse industries, including automotive, aerospace, and infrastructure, particularly in stress corrosion cracking detection, high-temperature material assessment, and pipeline monitoring. Additionally, her research explores the enhancement of testing systems with electromagnetic transducers and phased array technologies, which improve detection sensitivity and system reliability. Her contributions to NDT technology continue to shape the future of materials testing and structural health monitoring.

Awards and Honors

Xu Zhang has been recognized for her pioneering work in non-destructive testing, particularly in the application of electromagnetic and ultrasonic guided wave technologies. As a Principal Investigator (PI), she has secured several prestigious grants and awards, including the National Key Research and Development Plan Project and the National Natural Science Foundation of China Project. Her research on stress corrosion cracking detection, material assessment, and corrosion imaging has earned her numerous accolades. Zhang has also been honored with key research project leadership positions from the Provincial Science and Technology Department, reflecting her influence in advancing the state of engineering diagnostics. She continues to contribute to the scientific community, and her work in non-destructive testing systems is frequently recognized for its practical applications in the fields of materials science and engineering.

Conclusion

Xu Zhang is a leading figure in the field of intelligent non-destructive testing, with an impressive array of research accomplishments and leadership in cutting-edge projects. Her scholarly work in the development of advanced testing systems and her commitment to pushing the boundaries of engineering innovation make her an outstanding candidate for the Best Scholar Award. With a strong foundation in both academic research and practical applications, Zhang’s continued contributions to the field hold the promise of significant advancements in industrial safety and technology.

Publications Top Noted

A novel amplitude enhancement method of EMAT for High-frequency Rayleigh-like waves in Circumferential propagation

Authors: Zhang, X., Li, B., Niu, X., Song, X., Wu, Q.

Citations: 0

Year: 2024

Journal: NDT and E International, 148, 103231

Investigation of an Active Focusing Planar Piezoelectric Ultrasonic Transducer

Authors: Wu, Q., You, B., Zhang, X., Tu, J.

Citations: 0

Year: 2024

Journal: Sensors, 24(13), 4082

Characterization of Small Delamination Defects by Multilayer Flexible EMAT

Authors: Chen, T., Liu, S., Lv, C., Wu, Q., Zhang, X.

Citations: 1

Year: 2024

Journal: IEEE Sensors Journal, 24(12), pp. 19210–19219

Unidirectional focusing Rayleigh waves EMAT for plate surface defect Inspection

Authors: Chen, T., Lou, T., Lv, C., Wu, Q., Zhang, X.

Citations: 0

Year: 2024

Journal: Nondestructive Testing and Evaluation (Article in Press)

Design and experimental study of electromagnetic ultrasonic single-mode guided wave transducer for small-diameter stainless steel tubes

Authors: Tu, J., Zhan, X., Sun, H., Zhang, X., Song, X.

Citations: 3

Year: 2024

Journal: Nondestructive Testing and Evaluation (Article in Press)

Internal and External Pipe Defect Characterization via High-Frequency Lamb Waves Generated by Unidirectional EMAT

Authors: Zhang, X., Li, B., Zhang, X., Yuan, J., Wu, Q.

Citations: 3

Year: 2023

Journal: Sensors (Basel, Switzerland), 23(21)

Bolt Axial Stress Measurement Based on the Dual-Mode Electromagnetic Acoustic Transducer

Authors: Zhang, X., Li, W., Wu, Q., Cai, C., Song, X.

Citations: 2

Year: 2023

Journal: IEEE Sensors Journal, 23(13), pp. 13978–13986

Energy Transfer Efficiency Based Nonlinear Ultrasonic Testing Technique for Debonding Defects of Aluminum Alloy Foam Sandwich Panels

Authors: Tu, J., Yao, N., Ling, Y., Zhang, X., Song, X.

Citations: 0

Year: 2023

Journal: Sensors, 23(6), 3008

Optimized Design of Torsional Guided Wave Magnetostrictive Patch Transducer Based on Reversed Wiedemann Effect

Authors: Li, C., Yang, R., Gu, J., Wang, S., Zhang, X.

Citations: 5

Year: 2023

Journal: Journal of Nondestructive Evaluation, 42(1), 26

Enhancing the Lift-Off Performance of EMATs by Applying an Fe3O4 Coating to a Test Specimen

Authors: Liang, B., Li, Z., Zhai, G., Zhang, X., Dixon, S.

Citations: 5

Year: 2023

Journal: IEEE Transactions on Instrumentation and Measurement, 72, 9502104