Neyara Radwan | Innovation in Data Analysis | Outstanding Scientist Award

Dr. Neyara Radwan | Innovation in Data Analysis | Outstanding Scientist Award

Liwa College, ABU Dhabi | United Arab Emirates

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๐Ÿ‘ฉโ€๐Ÿซ Summary

Dr. Neyara Radwan is an accomplished academic and researcher specializing in Industrial Engineering, Lean Manufacturing, Sustainable Systems, and Renewable Energy. Currently an Associate Professor at Liwa College in Abu Dhabi, UAE, she has an impressive academic history with roles across several prestigious institutions globally, including in Egypt, Saudi Arabia, and India. With a passion for sustainable development and advanced engineering systems, her research focuses on optimization, supply chain management, solid waste management, and energy systems.

๐ŸŽ“ Education

Dr. Radwan holds a Ph.D. in Production Engineering from Benha University, Egypt (2008), with a thesis on CAD of Electro-Chemical Honing Machining and Statistical Modeling. She also earned her M.A. in Production Engineering and Mechanical Design from Mansoura University, Egypt (2004), focusing on utilizing computer-aided expert systems for power transmission shaft design. Additionally, she completed her B.A. in the same field from Mansoura University, where she designed belt conveyors for a sugar factory project.

๐Ÿ’ผ Professional Experience

Dr. Radwan has an extensive career in academia. She is currently an Associate Professor at Liwa College in Abu Dhabi (2023โ€“Present). Before this, she served as an Associate Professor at the Mechanical Department of Suez Canal University, Egypt (2012โ€“2023), and as a Quality Assurance Officer and Assistant Professor at King Abdulaziz University, Jeddah, KSA (2014โ€“2021). She has also held part-time roles in various academic institutions in Egypt, focusing on industrial engineering and mechanical design.

๐Ÿ… Awards & Recognition

Dr. Radwan’s dedication to education and research has earned her numerous awards, including the Excellence in Education Development Award (NCRDSIMS, India, 2018), the Global Service to Humanity Award (ADlafrica, 2021), and the Golden Academic Award (Tradepreneur Global, 2022). She has also been recognized for her outstanding academic leadership, receiving the Global Excellence in Academic Leadership Award (2024) and the Most Outstanding Engineering Educator and Writer Award (2024). Her contributions have been consistently celebrated through international accolades and recognitions.

๐Ÿ”ง Technical Skills

Dr. Radwanโ€™s technical expertise spans several cutting-edge areas, including Optimization, Lean Manufacturing, and Sustainable Engineering. She is skilled in Renewable Energy Systems, Artificial Intelligence Applications in Engineering, Supply Chain Management, and Solid Waste Management. Additionally, her proficiency in CAD Modeling and Statistical Process Control allows her to explore and implement advanced solutions for sustainable systems and optimal operations.

๐Ÿ‘ฉโ€๐Ÿซ Teaching Experience

Dr. Radwan has taught at top-tier universities across multiple countries, specializing in Industrial Management, Mechanical Engineering, and Sustainable Systems. Her teaching includes overseeing quality assurance in MBA/EMBA programs, and she is passionate about helping students connect theoretical knowledge with practical, real-world applications. She is recognized for her engaging teaching style and her ability to inspire the next generation of engineers and leaders.

๐Ÿ”ฌ Research Interests

Dr. Radwan’s research interests are wide-ranging, with a primary focus on Sustainability, Renewable Energy, and Optimization. Her work also delves into Circular Economy, Waste Management, Energy Systems, and Artificial Intelligence applications in engineering. She is particularly dedicated to researching how these fields intersect with global goals like the Sustainable Development Goals (SDGs), striving for impactful, real-world solutions to critical environmental and societal challenges.

Publication Top Notes

Development of artificial intelligence techniques in Saudi Arabia: the impact on COVID-19 pandemic. Literature review
    • Authors: NB Al-Jehani, ZA Hawsawi, N Radwan, M Farouk
    • Journal: Journal of Engineering Science and Technology
    • Citation: 12
    • Year: 2021 ๐Ÿ—“๏ธ
Characterizing land use/land cover change dynamics by an enhanced random forest machine learning model: a Google Earth Engine implementation
    • Authors: CB Pande, A Srivastava, KN Moharir, N Radwan, L Mohd Sidek, …
    • Journal: Environmental Sciences Europe
    • Citation: 11
    • Year: 2024 ๐Ÿ—“๏ธ
Heat transfer analysis of single-walled carbon nanotubes in Ellis’s fluid model: Comparative study of uniform and non-uniform channels
    • Authors: M Irfan, I Siddique, M Nazeer, S Saleem, N Radwan
    • Journal: Case Studies in Thermal Engineering
    • Citation: 10
    • Year: 2024 ๐Ÿ—“๏ธ
Dynamics of magnetized viscous dissipative material of hybrid nanofluid with irregular thermal generation/absorption
    • Authors: M Yasir, S Saleem, M Khan, N Radwan
    • Journal: Case Studies in Thermal Engineering
    • Citation: 8
    • Year: 2024 ๐Ÿ—“๏ธ
Assessment of groundwater potential zone mapping for semi-arid environment areas using AHP and MIF techniques
    • Authors: SP Shinde, VN Barai, BK Gavit, SA Kadam, AA Atre, CB Pande, SC Pal, …
    • Journal: Environmental Sciences Europe
    • Citation: 8
    • Year: 2024 ๐Ÿ—“๏ธ
A comparative study based on performance and techno-economic analysis of different strategies for PV-Electrolyzer (green) hydrogen fueling incinerator system
    • Authors: OM Butt, MS Ahmad, TK Lun, HS Che, H Fayaz, N Abd Rahim, KKK Koziol, …
    • Journal: Waste Management
    • Citation: 8
    • Year: 2023 ๐Ÿ—“๏ธ

Naiwei Lu | Data Analysis | Best Researcher Award

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

Changsha University of Science of Technology, China

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๐Ÿ‘จโ€๐Ÿซ 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.

๐ŸŽ“ 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.

๐Ÿ’ผ 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.

๐Ÿ’ฐ 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 ยฅ1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

๐Ÿ” 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 ๐Ÿค–, fatigue reliability of stay cables and orthotropic steel bridge decks ๐ŸŒ‰, and probabilistic modeling using data from structural health monitoring ๐Ÿ“Š. He is also focused on intelligent maintenance and management of in-service bridges โš™๏ธ, as well as uncertainty quantification in structural engineering ๐Ÿ› ๏ธ.

๐Ÿ“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.

๐Ÿ—๏ธ 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 ๐Ÿ—๏ธ, conducting structural health monitoring of suspension bridges ๐ŸŒ‰, and contributing to the detection and reinforcement of aging bridges ๐Ÿ› ๏ธ. 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 Luโ€™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.

๐Ÿ“–Top Noted Publicationsย 

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 Timeโ€“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