María Ortiz de Zúñiga | Data Analysis | Best Researcher Award

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Mrs. María Ortiz de Zúñiga | Data Analysis | Best Researcher Award

Mrs. María Ortiz de Zúñiga, UNED and Fusion for Energy, Spain

Publication Profile

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🌟 Summary

Mrs. María Ortiz de Zúñiga With over 17 years of experience in Fusion for Energy, I have contributed to various complex, multidisciplinary projects such as the ITER program, leading and managing teams, technical contracts, and large-scale nuclear mechanical systems. My expertise spans across engineering disciplines, including mechanical and computer engineering, and I hold two Master’s degrees in Mechanical Engineering and Computer Engineering. I specialize in project management, leadership, and AI for engineering development, focusing on driving innovation in advanced manufacturing technologies, nuclear safety, and stakeholder management.

🎓 Education

  • Philosopher’s Degree (PhD) in Industrial Technologies
    Universidad Nacional de Educación a Distancia – UNED (2021–Present)
  • Master of Engineering in Mechanical Engineering in Advanced Manufacturing Technologies
    Universidad Nacional de Educación a Distancia – UNED (2017–2021)
  • Master of Engineering in Computer Engineering
    Universidad Pontificia de Comillas – ICAI (2002–2007)

💼 Professional Experience

  • Senior Technical Officer, Fusion for Energy (2022–Present)
    Leading AI for engineering developments in the ITER project, responsible for managing expert contracts and representing F4E in the RCC-MRx nuclear code subcommittee.
  • Deputy Program Manager, Antennas Programme for ITER (2021–2022)
    Managed the design, procurement, and manufacturing of the Electron Cyclotron Antenna, including stakeholder and contract management.
  • Project Manager, ITER Vacuum Vessel Sectors (2019–2021)
    Oversaw the manufacturing of the last 3 European Vacuum Vessel sectors, managing financial, administrative, and technical contract responsibilities.
  • Technical Project Coordinator, ITER Vacuum Vessel (2016–2019)
    Led a team managing technical data, project contracts, and the supply chain for the Vacuum Vessel’s nuclear mechanical systems.
  • Planning Officer, Fusion for Energy (2007–2015)
    Managed planning and scheduling for ITER-related projects, supported risk management, and developed procurement schedules.

📝 Academic Citations

  • Co-chair, Artificial Intelligence Track (CT-19) at ASME-PVP
  • Reviewer at international conferences like SMiRT, ITU, and IAEA
  • Published research on AI in manufacturing and engineering processes for ITER components.

💻 Technical Skills

  • Engineering Software: Proficient in CAD systems, Primavera, Enovia Smarteam PLM, and AI tools for engineering applications.
  • Project Management: Skilled in planning, scheduling, risk management, earned value management, and contract negotiations.
  • Nuclear Safety: Experienced in working with the RCC-MRx code, nuclear safety audits, and quality control for nuclear-related projects.
  • Languages: Fluent in up to 6 European languages.

👩‍🏫 Teaching Experience

  • Co-led the Artificial Intelligence Community within Fusion for Energy to raise awareness and promote AI usage in engineering projects.
  • Actively contributed to Diversity, Equity, and Inclusion initiatives within F4E, supporting training and workshops on these topics.

🔬 Research Interests On Data Analysis

  • Artificial Intelligence for manufacturing optimizations in nuclear components.
  • Data Analysis in high-tech engineering, focusing on predictive models for welding success, ultrasonic testing, and superconducting magnets.
  • Development and integration of advanced manufacturing technologies into nuclear engineering systems.

Publication Top Notes

Project management techniques used in the European Vacuum Vessel sectors procurement for ITER

📑 Authors: M Losasso, MO de Zuniga, L Jones, A Bayon, JF Arbogast, J Caixas, …
📰 Journal: Fusion Engineering and Design
📅 Year: 2012

Artificial Intelligence for the Output Processing of Phased-Array Ultrasonic Test Applied to Materials Defects Detection in the ITER Vacuum Vessel Welding Operations

📑 Authors: M Ortiz de Zuniga, N Prinja, C Casanova, A Dans Alvarez de Sotomayor, …
📰 Journal: Pressure Vessels and Piping Conference
📅 Year: 2022

Artificial Intelligence for quality control in manufacturing applied to materials defects detection in the ITER Vacuum Vessel welding operations

📑 Authors: MO de Zúñiga López-Chicheri, M Febvre, ADA de Sotomayor, N Prinja, …
📰 Journal: IASMiRT
📅 Year: 2022

 

Naiwei Lu | Data Analysis | Best Researcher Award

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Assoc Prof Dr. Naiwei Lu | Data Analysis | Best Researcher Award

Changsha University of Science of Technology, China

Author Profiles

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👨‍🏫 Associate Prof. Dr. Naiwei Lu

Assoc. Prof. Dr. Naiwei Lu is an Associate Professor in Civil Engineering at Changsha University of Science and Technology (CSUST), China. His research primarily focuses on reliability and safety in bridge engineering. He has a strong background in system reliability evaluation, fatigue analysis, and structural health monitoring, which he applies to the engineering and maintenance of long-span bridges. Dr. Lu is an active member of various international research communities and has been involved in multiple national and international projects.

🎓 Education Background

Dr. Naiwei Lu earned his Ph.D. in Civil Engineering from Changsha University of Science and Technology (CSUST) in 2015, under the supervision of Prof. Yang Liu. Prior to that, he completed his Master’s degree in Civil Engineering in 2011 and his Bachelor’s degree in Bridge Engineering in 2008, all at CSUST, Changsha, China. His academic journey laid a strong foundation for his expertise in bridge engineering and reliability analysis.

💼 Employment and Research Experience

Dr. Lu’s academic career began in 2015 when he became a Postdoctoral Researcher at Southeast University in Nanjing, China, where he worked under Prof. Mohammad Noori. He also held a Postdoctoral Researcher position at Leibniz University Hannover, Germany, working with Prof. Michael Beer. Since 2020, Dr. Lu has been serving as an Associate Professor at CSUST, where he also previously worked as a Lecturer from 2017 to 2019. His diverse academic and international experiences contribute to his deep expertise in bridge engineering.

💰 Research Funding

Dr. Lu has been the Principal Investigator (PI) of several funded research projects, including the National Science Funding in China for research on structural health monitoring of suspension bridges and the fatigue reliability evaluation of steel bridge decks. He has received significant funding support for his work in system reliability and dynamic analysis, with total funding exceeding ¥1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

🔍 Research Interests

Dr. Lu’s research spans several cutting-edge topics in structural engineering. His main research interests include system reliability evaluation of long-span bridges using intelligent algorithms 🤖, fatigue reliability of stay cables and orthotropic steel bridge decks 🌉, and probabilistic modeling using data from structural health monitoring 📊. He is also focused on intelligent maintenance and management of in-service bridges ⚙️, as well as uncertainty quantification in structural engineering 🛠️.

📚 Teaching Experience

As an educator, Dr. Lu teaches undergraduate courses such as Principle of Structural Design (in both Chinese and English) and Building Information Modeling (BIM) Technology (in Chinese). He has supervised 24 undergraduate students and 4 postgraduate students between 2017 and 2020, guiding them in various aspects of civil engineering, particularly related to bridge design, maintenance, and reliability.

🏗️ Engineering Activities

In addition to his academic role, Dr. Lu is a Registered Construction Engineer and a Registered Inspection Engineer in Municipal Engineering and Bridge & Tunnel Engineering, respectively. His engineering activities include overseeing the structural safety of long-span bridges during construction 🏗️, conducting structural health monitoring of suspension bridges 🌉, and contributing to the detection and reinforcement of aging bridges 🛠️. He has also been involved in the advance geological forecasting and monitoring of tunnels during construction, working on over five extra-long tunnels.

Dr. Naiwei Lu’s work integrates advanced intelligent algorithms, data-driven methods, and structural health monitoring to enhance the safety, reliability, and longevity of bridges and infrastructure systems. His research and engineering expertise continue to make significant contributions to the field of civil engineering.

📖Top Noted Publications 

Structural damage diagnosis of a cable-stayed bridge based on VGG-19 networks and Markov transition field: numerical and experimental study

Authors: Naiwei Lu, Zengyifan Liu, Jian Cui, Lian Hu, Xiangyuan Xiao, Yiru Liu

Journal: Smart Materials and Structures

Year: 2025

Coupling effect of cracks and pore defects on fatigue performance of U-rib welds

Authors: Yuan Luo, Xiaofan Liu, Fanghuai Chen, Haiping Zhang, Xinhui Xiao, Naiwei Lu

Journal: Structures

Year: 2025

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Authors: Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

Journal: Sensors

Year: 2024

A Novel Method of Bridge Deflection Prediction Using Probabilistic Deep Learning and Measured Data

Authors: Xinhui Xiao, Zepeng Wang, Haiping Zhang, Yuan Luo, Fanghuai Chen, Yang Deng, Naiwei Lu, Ying Chen

Journal: Sensors

Year: 2024

Experimental and numerical investigation on penetrating cracks growth of rib-to-deck welded connections in orthotropic steel bridge decks

Authors: Zitong Wang, Jun He, Naiwei Lu, Yang Liu, Xinfeng Yin, Haohui Xin

Journal: Structures

Year: 2024

Fatigue Reliability Assessment for Orthotropic Steel Decks: Considering Multicrack Coupling Effects

Authors: Jing Liu, Yang Liu, Guodong Wang, Naiwei Lu, Jian Cui, Honghao Wang

Journal: Metals

Year: 2024