Fabrizia Devito | Data Quality Enhancement | Women Researcher Award

Dr. Fabrizia Devito | Data Quality Enhancement | Women Researcher AwardΒ 

Dr. Fabrizia Devito , Politecnico di Bari, Italy.

Publication Profile

Orcid
Scopus

Summary 🌍

A passionate researcher in Additive Manufacturing (AM) πŸ–¨οΈ, AI πŸ€–, and sustainability 🌱. With experience across international academic institutions 🌍, Fabrizia has worked on cutting-edge projects in manufacturing technology βš™οΈ and energy systems πŸ”‹, striving to improve production processes and environmental impact 🌎.

Education πŸŽ“

  • Ph.D. Student in Sustainable Development & Climate Change 🌱, Polytechnic of Bari, Italy (2021-2025)
  • Master’s Degree in Management Engineering (Operations Management) βš™οΈ, Polytechnic of Bari, Italy (2021)
  • Bachelor’s Degree in Management Engineering, Polytechnic of Bari, Italy (2019)
  • Sustainable Development & Climate Change at IUSS-Scuola Universitaria Superiore, Pavia, Italy (2021-2024)

Professional Experience πŸ’Ό

  • Researcher at Vantia S.r.l. (Spin-Off University of Bari) πŸ”¬, Bari, Italy (2024–Present)
  • Research Assistant at University of Cantabria, Spain πŸ‡ͺπŸ‡Έ (2024)
  • Research Assistant at University of Sharjah, UAE πŸ‡¦πŸ‡ͺ (2022)
  • Internships at Jaggaer Academy and Fincons S.p.A. 🏒 (2021), and Polytechnic of Bari πŸ›οΈ (2019)

Academic Citations πŸ“š

  • Co-author of research on Additive Manufacturing and sustainable processes at Polytechnic of Bari πŸ“ (2021-Present)
  • Presentation at IFAC/INSTICC IN4PL 2024 (Porto, Portugal) πŸ‡΅πŸ‡Ή and Global Conference on Sustainable Manufacturing 2023 🌍

Technical Skills πŸ’»

  • Software: AutoCAD πŸ–₯️, Solidworks βš™οΈ, MATLAB πŸ“Š, Python 🐍, Ansys πŸ—οΈ, CAE Tools, Rhinoceros 🦏, and more
  • Engineering & Energy Modeling: SimaPro 🌱, OpenLCA ♻️, Zenon, and CYPELUX πŸ”‹
  • Programming: C, C++, Python, Arduino πŸ–§
  • Simulation & Optimization: Discrete & Continuous Simulation, Finite Element Analysis πŸ§‘β€πŸ’»
  • Other Tools: Weka, PostgreSQL, Minitab πŸ“ˆ, RStudio, and more

Teaching & Research Interests On Data Quality Enhancement πŸ”¬

  • Additive Manufacturing πŸ–¨οΈ, AI in Manufacturing πŸ€–, Sustainable Energy Solutions 🌞
  • Circular Economy ♻️ & Recycling in Additive Manufacturing πŸ”„
  • Energy System Modeling & Optimization πŸ”‹
  • Machine Learning πŸ“Š applications in Process Optimization

Extracurricular Activities ⚽️

  • Sports: Rowing πŸš£β€β™€οΈ, Sailing β›΅, Yoga πŸ§˜β€β™€οΈ
  • Hobbies: 3D Printing πŸ–¨οΈ, Robotics πŸ€–, AI πŸ€–, and Material Engineering πŸ§ͺ
  • Leadership: Class representative πŸ—£οΈ during high school (2015-2016)

Publication Top Notes

Causal technological model for predicting void fraction and energy consumption in material extrusion process of polylactic acid
    • Authors: πŸ§‘β€πŸ”¬ Devito, Mazzarisi, Dassisti, Lavecchia
    • Journal: πŸ“š Journal of Manufacturing Processes
    • Year: πŸ“… 2024
Notch Effect in Acrylonitrile Styrene Acrylate (ASA) Single-Edge-Notch Bending Specimens Manufactured by Fused Filament Fabrication
    • Authors: πŸ§‘β€πŸ”¬ Cicero, Devito, SΓ‘nchez, Arrieta, Arroyo
    • Journal: πŸ“š Materials (MDPI)
    • Year: πŸ“… 2024
Business Models and Advanced Additive Manufacturing strategies for better sustainability
    • Authors: πŸ§‘β€πŸ”¬ Devito, Copani, Natalicchio, Al-Alami, Lavecchia, Olabi, Dassisti
    • Journal: πŸ“š Energy Nexus
    • Year: πŸ“… 2024
Advancing Sustainability in Electron and Laser Beam Powder Bed Fusion Technologies via Innovation: Insights from Patent Analysis
    • Authors: πŸ§‘β€πŸ”¬ Devito, Natalicchio, Lavecchia, Dassisti
    • Journal: πŸ“š Computers & Industrial Engineering
    • Year: πŸ“… 2024
In-process detection of defects on parts produced by laser metal deposition using off-axis optical monitoring
    • Authors: πŸ§‘β€πŸ”¬ Mazzarisi, Guerra, Latte, Devito, Galantucci, Campanelli, Lavecchia, Dassisti
    • Journal: πŸ“š International Journal of Advanced Manufacturing Technology
    • Year: πŸ“… 2023
Recent developments of Additive Manufacturing for circular economy
    • Authors: πŸ§‘β€πŸ”¬ Devito, Al-Alami, Olabi, Lavecchia, Dassisti
    • Journal: πŸ“š Journal of Cleaner Production
    • Year: πŸ“… 2024

Naiwei Lu | Data Analysis | Best Researcher Award

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

Changsha University of Science of Technology, China

Author Profiles

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Scopus

Research Gate

πŸ‘¨β€πŸ« 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.

πŸŽ“ 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.

πŸ’Ό 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.

πŸ’° 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 Β₯1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

πŸ” 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 πŸ€–, fatigue reliability of stay cables and orthotropic steel bridge decks πŸŒ‰, and probabilistic modeling using data from structural health monitoring πŸ“Š. He is also focused on intelligent maintenance and management of in-service bridges βš™οΈ, as well as uncertainty quantification in structural engineering πŸ› οΈ.

πŸ“š 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.

πŸ—οΈ 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 πŸ—οΈ, conducting structural health monitoring of suspension bridges πŸŒ‰, and contributing to the detection and reinforcement of aging bridges πŸ› οΈ. 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.

πŸ“–Top Noted PublicationsΒ 

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