Juan Carlos Antolin Urbaneja | Vision Sensing | Best Researcher Award

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Dr. Juan Carlos Antolin Urbaneja | Vision Sensing | Best Researcher Award

Dr. Juan Carlos Antolin Urbaneja, TECNALIA, Basque Research and Technology Alliance, BRTA, Spain.

Juan Carlos Antolín Urbaneja is a Senior Researcher at TECNALIA, part of the Basque Research & Technology Alliance (BRTA). With over 25 years of experience in robotics and automation, Juan Carlos specializes in 3D vision, 3D reconstruction, robotized inspection, and image analysis. He has worked on diverse technologies, including surface treatment, water quality identification, robots, and additive manufacturing. His contributions extend to various industrial sectors such as biomedical, automotive, and aeronautical, where he develops custom software and hardware solutions. He has led numerous public and private research projects and co-authored a European patent.

Professional Profile

ORCID

Suitability of Juan Carlos Antolín Urbaneja for the Best Researcher Award

Juan Carlos Antolín Urbaneja, I believe he is highly suitable for the Best Researcher Award. He has successfully managed and executed around 40 research projects, including both public and private funding, indicating a strong ability to drive innovative research initiatives.

Education 🎓

Juan Carlos holds a degree in Industrial Engineering with an electrical specialty (2000) from Bilbao Faculty of Engineering, Basque Country University. He also completed a degree in Innovation and Technology Management (2004) from Deusto Faculty (ESIDE). His academic journey culminated in a Ph.D. in Control Engineering, Automation, and Robotics from the University of the Basque Country in 2017. This foundation in engineering and management has propelled him into an influential career in robotics and automation, blending theoretical knowledge with practical applications in cutting-edge technologies.

Experience 💼

With a robust career spanning 25 years, Juan Carlos has been deeply involved in the research, development, and execution of advanced robotic systems. He has participated in over 40 projects, both public and private, and has contributed significantly to the development of innovative machines used in various industries. His expertise includes electrical and electronic design, where he applies programming tools like Matlab-Simulink and LabVIEW. Juan Carlos is also a peer reviewer and co-author of scientific papers, contributing to the field’s growth. His notable contributions include robotic inspection systems and advanced additive manufacturing techniques.

Research Interests 🔬

Juan Carlos’s research interests are centered around robotics, automation, and additive manufacturing. His work explores the development of systems for robotized inspection and 3D scanning, with applications in large-scale parts inspection and dimensional qualification. He is particularly interested in enhancing the capabilities of robots to interact with complex materials and environments, such as biomedical and automotive sectors. His research also spans innovations in wave energy and surface treatment, continuously striving for breakthroughs that bridge the gap between theoretical research and practical industrial solutions.

Awards 🏆

Juan Carlos has received numerous accolades throughout his career. He is the recipient of more than 20 awards, including recognition for his contributions to robotics, automation, and innovation. His work in additive manufacturing and robotized inspection has earned him widespread recognition in scientific communities. As a testament to his contributions, he was nominated for several prestigious awards, including the Distinguished Scientist Award and the Outstanding Scientist Award. These honors reflect his excellence in both research and industrial applications, highlighting his impact on technological advancements.

Publications Top Notes📚

Automated MOLDAM Robotic System for 3D Printing: Manufacturing Aeronautical Mould Preforms

Robotized 3D Scanning and Alignment Method for Dimensional Qualification of Big Parts Printed by Material Extrusion

Experimental Characterization of Screw-Extruded Carbon Fibre-Reinforced Polyamide: Design for Aeronautical Mould Preforms with Multiphysics Computational Guidance

Coordination of Two Robots for Manipulating Heavy and Large Payloads Collaboratively: SOFOCLES Project Case Use

Robot Coordination: Aeronautic Use Cases Handling Large Parts

 

Prof Wanrun Li | Vision Sensing | Best Researcher Award

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Prof Wanrun Li | Vision Sensing | Best Researcher Award

Prof Wanrun Li, Lanzhou University of Technology, China 

Professor Wanrun Li is a distinguished academic and researcher in Structural Health Monitoring, currently serving as the Vice Dean of the School of Civil Engineering at Lanzhou University of Technology, China. With a focus on fatigue analysis, wind turbine vibration control, and structural health monitoring, he has led numerous research projects funded by national and regional foundations. His work has significantly contributed to understanding the seismic performance of super-tall buildings, damage identification, and fatigue life prediction of wind turbines. He has held multiple leadership roles, including Associate Professor and department head, and has been a visiting scholar at prestigious institutions.

Professional Profile:

Suitability for the Best Researcher Award: 

Professor Wanrun Li’s extensive research portfolio, leadership in high-stakes projects, and contributions to structural engineering make him a strong candidate for the Best Researcher Award. His work in wind turbine vibration control and fatigue analysis is critical for the advancement of sustainable energy infrastructure. However, to strengthen his candidacy, broadening the impact of his research on industry standards and further enhancing global outreach would be valuable steps forward. Overall, his dedication to innovative research and significant contributions to civil engineering position him as a deserving nominee for this prestigious award.

Education

Professor Wanrun Li earned his Ph.D. in Structural Engineering from Lanzhou University of Technology in 2013, specializing in Structural Health Monitoring under the guidance of Prof. Yongfeng Du and Prof. Y.Q. Ni. He was also a joint-supervised Ph.D. candidate at Hong Kong Polytechnic University from 2011-2012. His academic background includes an M.S. in Disaster Prevention and Mitigation from Lanzhou University of Technology (2010) and a B.S. in Civil Engineering from the same institution (2008). His education laid the foundation for his expertise in monitoring structural health and analyzing the fatigue of civil structures.

Work Experience

Wanrun Li has over a decade of academic and research experience. Currently, he is a Professor and Vice Dean at Lanzhou University of Technology. He previously served as an Associate Professor and Head of the Department of Building Engineering. His international experience includes being a visiting scholar at the University of Illinois Urbana-Champaign and Southeast University, China. Over the years, he has led research initiatives focused on vibration control, fatigue life prediction, and damage identification in large structures such as wind turbines and high-rise buildings.

Skills

Professor Li’s technical expertise includes advanced knowledge in Structural Health Monitoring, Wind Turbine Vibration Control, and Weld Fatigue Analysis. His skills extend to predictive modeling, statistical pattern recognition, and seismic data analysis. He is proficient in developing new devices for vibration reduction, using machine vision technology for turbine blade detection, and applying experimental and multi-scale simulation techniques for assessing fatigue in steel structures. His proficiency with numerical modeling, experimental research, and structural design underpins his research and teaching efforts.

Awards and Honors

Wanrun Li has been recognized with multiple prestigious awards, including the Hongling Outstanding Young Scholar Award at Lanzhou University of Technology (2019-2021) and the Science Fund for Distinguished Young Scholars of Gansu Province (2021-2024). His work has earned several grants from the National Natural Science Foundation of China (NSFC), totaling over ¥1.9 million for projects related to wind turbine structures and vibration control. These honors affirm his significant contributions to structural engineering and disaster prevention.

Membership

Professor Li is actively engaged in several professional organizations, contributing to the advancement of structural health monitoring and civil engineering. He collaborates closely with renowned research groups and institutions, including the University of Illinois Urbana-Champaign and Southeast University. His membership in national scientific communities has enabled him to secure significant research funding and present his findings in both domestic and international conferences.

Teaching Experience

With a passion for mentoring, Professor Li has been an academic instructor at Lanzhou University of Technology since 2013, progressing from instructor to professor. As a faculty member, he has taught courses related to Structural Engineering, Civil Engineering, and Structural Health Monitoring. His role as the Chief Duty Professor for the Hongliu Top-class Major in Civil Engineering reflects his commitment to academic excellence. He also supervises graduate students, guiding them through research projects and fostering a collaborative learning environment.

Research Focus

Professor Li’s research is centered on Structural Health Monitoring, Weld Fatigue Analysis, and Vibration Control of Wind Turbines. He is particularly interested in seismic data analysis of tall structures, wind-induced fatigue of turbines, and developing new devices for reducing tower vibrations. His projects include studies on vibration control using tuned liquid column dampers and fatigue life prediction of wind turbines in harsh environments. His innovative work integrates machine vision technology and UAVs for turbine blade detection, and he has contributed significantly to enhancing structural safety and durability.

Publication top Notes:

“Wind turbine blade defect detection and measurement technology based on improved SegFormer and pixel matching”

    • Year: 2024
    • Journal: Optics & Laser Technology
    • DOI: 10.1016/j.optlastec.2024.111381

“Mitigation of In-Plane Vibrations in Large-Scale Wind Turbine Blades with a Track Tuned Mass Damper”

    • Year: 2023
    • Journal: Structural Control and Health Monitoring
    • DOI: 10.1155/2023/8645831

“Dynamic Characteristic Monitoring of Wind Turbine Structure Using Smartphone and Optical Flow Method”

    • Year: 2022
    • Journal: Buildings
    • DOI: 10.3390/buildings12112021

“Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV”

    • Year: 2022
    • Journal: Remote Sensing
    • DOI: 10.3390/rs14133113

“Seismic Vibration Mitigation of Wind Turbine Tower Using Bi-Directional Tuned Mass Dampers”

    • Year: 2020
    • Journal: Mathematical Problems in Engineering
    • DOI: 10.1155/2020/8822611

“Low-cycle fatigue test and life assessment of carbon structural steel GB Q235B butt joints and cruciform joints”

    • Year: 2019
    • Journal: Advances in Structural Engineering
    • DOI: 10.1177/1369433218795292

“Seismic Performance of a New Precast Concrete Shear Wall with Bolt Connection”

    • Year: 2019
    • Journal: Gongcheng Kexue Yu Jishu/Advanced Engineering Science
    • DOI: 10.15961/j.jsuese.201801163

“Time-Varying Nonlinear Parametric Identification of Isolated Structure Based on Wavelet Multiresolution Analysis”

    • Year: 2019
    • Journal: Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
    • DOI: 10.16450/j.cnki.issn.1004-6801.2019.03.024

“Welding Residual Stress Simulation and Experimental Verification in Beam-to-Column Joints of Q345B Steel”

    • Year: 2019
    • Journal: Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)
    • DOI: 10.12141/j.issn.1000-565X.190044