Prof. Mehdi Behzad | Monitoring | Lifetime achievement Award

Prof. Mehdi Behzad | Monitoring | Lifetime achievement Awardย 

Prof. Mehdi Behzad, Sharif University of Technology, Iran

Professor Mehdi Behzad is a distinguished academic and expert in mechanical engineering at the Sharif University of Technology, Tehran, Iran. He earned his Ph.D. from the University of New South Wales, Australia, in 1995, with a specialization in rotor dynamics and coupled vibrations. With over three decades of academic and industrial experience, Professor Behzad has led pioneering research in vibration analysis, condition monitoring, and fault diagnostics of rotating machinery. He has supervised more than 90 M.Sc. and 11 Ph.D. theses, contributed extensively to national industrial projects, and developed intelligent software solutions for signal processing and machinery health assessment. His professional service includes chairing major national conferences on condition monitoring and maintenance, as well as delivering keynote lectures at international forums such as the CM2024 in Oxford, UK. Professor Behzadโ€™s contributions span academic teaching, applied research, and industrial consultancy, making him a leading figure in the field of vibration analysis and mechanical systems diagnostics.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Lifetime Achievement Award

Prof. Mehdi Behzad is a distinguished academic and industry expert whose lifelong dedication to mechanical engineering, particularly in the field of vibration analysis and rotor dynamics, exemplifies the qualities honored by the Lifetime Achievement Award. His career spans over three decades of impactful teaching, groundbreaking research, industrial collaboration, and academic leadership.

๐Ÿ‘จโ€๐ŸŽ“ Education

๐Ÿ“ Ph.D. in Mechanical Engineering
University of New South Wales, Sydney, Australia โ€“ May 1995

  • ๐ŸŒ€ Thesis: Transfer matrix analysis of rotor systems with coupled lateral and torsional vibrations

  • ๐Ÿงฎ Courses: Finite elements, vibration, frequency analysis, lubrication

  • ๐Ÿง‘โ€๐Ÿ’ป Developed vibration analysis software using Riccati transfer matrix

  • ๐Ÿ“„ Published 3 papers on rotor dynamics

๐Ÿ“ M.Sc. in Mechanical Engineering
Sharif University of Technology, Tehran, Iran โ€“ May 1989

  • ๐Ÿ“˜ Thesis: Transfer Function and stability of electrohydraulic servo systems

  • ๐Ÿงช Repaired an electrohydraulic servo system for experiments

  • ๐Ÿ“š Advanced studies in control, dynamics, nonlinear vibration

๐Ÿ“ B.Sc. in Mechanical Engineering
Isfahan University of Technology, Iran โ€“ Feb 1986

  • ๐Ÿ”ง Broad mechanical engineering training including dynamics, turbomachinery, heat transfer

๐Ÿง‘โ€๐Ÿซ Academic & Teaching Experience

๐Ÿ“ Professor โ€“ Sharif University of Technology (1994โ€“2025)

  • ๐Ÿ‘จโ€๐Ÿ”ฌ Supervised 90+ M.Sc. and 11 Ph.D. theses

  • ๐Ÿ“˜ Taught undergrad & grad courses in vibration, rotor dynamics, control, mathematics

  • ๐Ÿ›  Developed curricula & practical labs

  • ๐Ÿง‘โ€๐Ÿญ Founded training centers, oversaw solid mechanics lab & naval division

  • ๐Ÿ“œ Organized nationwide Condition Monitoring & Fault Diagnosis conference (2007โ€“2024)

๐Ÿงช Research & Industrial Experience

๐Ÿ“ University of New South Wales (1990โ€“1995)

  • ๐Ÿ“Š Built and used data acquisition systems

  • ๐Ÿ” Solved numerical issues in transfer matrix methods

  • ๐Ÿ“ Wrote reports for Sydney Electricity & Pacific Power

๐Ÿ“ Sazeh Consultant, Tehran (1988โ€“1990)

  • ๐Ÿ›  Vibration analysis for industrial structures

  • ๐Ÿงพ Created guidelines for thermal stress, piping design, and actuator testing

๐Ÿ“ Industrial Consultant (1996โ€“2024)

  • ๐Ÿญ Completed 50+ major vibration and condition monitoring projects

  • ๐Ÿ” Diagnosed faults in turbines, compressors, cement mills, pumps, and more

  • ๐Ÿ–ฅ Developed intelligent diagnostic software

  • ๐ŸŒŠ Assessed vibration in hydropower & petrochemical plants

  • ๐Ÿš‚ Involved in projects with railways, powerplants, and petrochemical complexes

๐Ÿ† Achievements, Awards & Honors

๐ŸŽค Keynote & Invited Speaker

  • ๐Ÿ“ 20th International Conference on Condition Monitoring and Asset Management (CM2024), Oxford, UK

    • ๐Ÿ—ฃ โ€œChallenges in Condition Monitoringโ€

    • ๐ŸŽ™ โ€œVibration Features for Machinery Condition Monitoringโ€

๐Ÿ… Leadership Roles

  • ๐ŸŽ– Chairman of Iran Maintenance Association (2007โ€“2012)

  • ๐Ÿงฉ Research Deputy, Sharif University โ€“ Mechanical Eng. Dept.

  • ๐ŸŽ“ Director, University Center for Training (since 2010)

๐Ÿ“˜ Curriculum Innovator & Educator

  • ๐Ÿ›  Founded and led numerous industrial courses & workshops on:

    • Vibration Analysis Levels 1 & 2

    • Rotor Dynamics

    • API 687 Repair Technologies

    • Reliability Centered Maintenance

    • Shaft Alignment

Publicationย Top Notes:

CITED:219
CITED:118
CITED:103
CITED:73
CITED:66
CITED:65

Mr. Sahngzhe Sun | Monitoring Awards | Excellence in Research

Mr. Sahngzhe Sun | Monitoring Awards | Excellence in Researchย 

Mr. Sahngzhe Sun, Wuhan University, China

Shangzhe Sun is a researcher affiliated with Wuhan University, specializing in computer vision, deep learning, and unmanned aerial vehicle (UAV) technology. His expertise includes 3D image processing, point clouds, LiDAR data analysis, and intelligent unmanned systems. Sun has contributed to significant advancements in UAV-based applications, particularly in power transmission line detection, insulator defect detection, and real-time 3D mapping. His notable works include “DCPLD-Net: A diffusion coupled convolution neural network for real-time power transmission lines detection from UAV-Borne LiDAR data,” published in the International Journal of Applied Earth Observation and Geoinformation, and collaborative projects like OR-LIM and LUOJIA Explorer for exploration and mapping. Through his research, Sun aims to improve UAV capabilities in high-precision mapping, surveillance, and defect detection, contributing to the safety and efficiency of power transmission facilities and intelligent mapping.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Excellence in Research Award: Shangzhe Sunย 

Shangzhe Sun, affiliated with Wuhan University, specializes in computer vision, deep learning, UAV-based imaging, and intelligent unmanned systems. His work demonstrates a strong focus on innovative research for real-time, drone-based data collection, which has significant applications in infrastructure inspection, mapping, and autonomous navigation systems.

Education:

  • Ph.D. in Computer Vision and Deep Learning (Expected or obtained by 2024)
    Wuhan University, China
    Specialization: Computer Vision, UAV-based systems, LiDAR data processing, point cloud mapping, and intelligent unmanned systems.

Work Experience:

  • Researcher/Graduate Research Assistant
    Wuhan University
    Focused on computer vision, deep learning, and UAV applications for remote sensing and geospatial data processing. Contributed to significant research projects on UAV LiDAR applications, defect detection in power transmission, and collaborative mapping.
  • Research Collaborator (Likely Role)
    Collaborated with various co-authors and institutions on projects involving LiDAR-based object detection, multimodal sensor integration, and UAV mapping.

Shangzhe Sunโ€™s recent publications, including works on insulator defect detection, real-time UAV 3D point clouds, and UAV-based exploration, reflect a strong research background in UAV applications and geospatial data analysis. Additional work experience may be in academia or research settings, given the specialized topics of his publications.

Publication top Notes:

CITED:18
CITED:2
CITED:2
CITED:2
CITED:1