Mona AbouEleaz | Engineering and Technology | Best Researcher Award

Assoc. Prof. Dr Mona AbouEleaz, Mansoura University, Egypt

Assoc. Prof. Dr. Mona AbouEleaz 🌍⚙️ is a distinguished academic in Production Engineering at Mansoura University, Egypt. With a Ph.D. in Production Engineering 🎓, her expertise spans Smart Manufacturing, Industry 4.0, Lean Six Sigma, and Quality Improvement approaches 📊. She has held roles as a postdoctoral researcher in Canada 🇨🇦 and visiting lecturer in the UK 🇬🇧. As the Executive Director of the University Center for Career Development, she fosters student growth 🚀. Dr. AbouEleaz has published extensively 📚, supervised over 35 projects 🛠️, and actively contributes to academic accreditation and international collaborations 🌐. She enjoys reading, drawing, sports, and traveling ✈️🎨.

Publication Profile

Google Scholar

Education

Assoc. Prof. Dr. Mona AbouEleaz holds a Ph.D. in Production Engineering from Mansoura University, Egypt (2010–2015), with a thesis titled “Lean Six Sigma Practices into an Organizational Quality Management System” 🎯📊. She earned her M.Sc. in Industrial Engineering from Alexandria University (2005–2008), focusing on “Hierarchic Framework for Quality Improvement Approaches” ⚙️📈. Dr. AbouEleaz also holds a B.Sc. in Production Engineering & Mechanical Design from Mansoura University, graduating with honors and ranking first in her class 🏅🎓. Her academic journey reflects a strong commitment to quality improvement, engineering excellence, and continuous innovation 🔍💡.

Experience

Assoc. Prof. Dr. Mona AbouEleaz is a distinguished academic with extensive experience in mechanical design and production engineering. She’s a lecturer at Mansoura University, Egypt 🇪🇬, and has served as a visiting lecturer at the University of Central Lancashire, UK 🇬🇧, and a postdoctoral researcher at the University of Calgary, Canada 🇨🇦. Dr. AbouEleaz excels in leadership roles, serving as Executive Director of the University Career Center and coordinating ERASMUS programs 🌍. Her contributions to strategic planning, quality assurance ✅, and international collaboration 🤝 have significantly advanced Mansoura University’s academic landscape.

Research Focus

Assoc. Prof. Dr. Mona AbouEleaz’s research focuses on advanced manufacturing processes, particularly in Wire Electrical Discharge Machining (WEDM) and material performance analysis. Her work explores surface roughness, material removal rates, and optimization of machining parameters for alloys like AISI304 and AISI316. She also delves into roundness measurement techniques, finite element analysis, and the impact of ERP systems on production efficiency. Additionally, her studies address supply chain performance and process improvement strategies in manufacturing. ⚙️🔩📊✨🔍

Research Interest

Assoc. Prof. Dr. Mona AbouEleaz’s research focuses on Smart Manufacturing and Industry 4.0 🚀🏭. She specializes in enhancing the performance of production and service systems through Quality Improvement approaches, including Lean Six Sigma 📊, optimization methods ⚙️, and Response Surface Methodology. Her expertise extends to Uncertainty Analysis, MCDM (Multi-Criteria Decision Making), and Decision Making Under Uncertainty 🤔. Dr. Mona also works on Measurement Uncertainty, Mechanical Testing 🧪, and utilizes tools like Minitab and ANSYS for statistical and engineering analysis. Her research aims to boost efficiency, precision, and decision-making in advanced manufacturing environments 🌟.

Publication Top Notes

Experimental investigation of surface roughness and material removal rate in wire EDM of stainless steel 304

Methods of roundness measurement: An experimental Comparative study

Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization

The Impact of Enterprise Resource Planning (ERP) Implementation on Performance of Firms: A Case to Support Production Process Improvement.

A critical review of supply chain performance evaluation

A study of drilling parameter optimization of functionally graded material steel–aluminum alloy using 3D finite element analysis

Automated Classification of Marble Types Using Texture Features and Neural Networks: A Robust Approach for Enhanced Accuracy and Reproducibility

Types Using Texture Features and Neural Networks: A Robust Approach

Investigating the Impact of Cutting Parameters on Roundness and Circular Runout Using Signal-to-noise Ratio Analysis

Education

Mr. Tailong Lv holds a Bachelor’s degree in Automation from Henan University of Urban Construction and is currently pursuing a Master’s degree in Mechanical Engineering at Xi’an University of Posts & Telecommunications. His academic foundation is strong, particularly in technical fields relevant to his research focus.

Research Project

Mr. Lv’s main research project, “Deep Learning Based Human Activity Recognition,” showcases his proficiency in applying deep learning techniques to real-world problems. His work focuses on optimizing neural networks for better recognition of complex human activities. This is a cutting-edge area in artificial intelligence and has significant potential for applications in areas such as surveillance, healthcare, and human-computer interaction. His contribution to this field is commendable, given the complexity and real-world relevance of the project.

Research focus

The research focus of this person primarily revolves around urban planning, environmental sustainability, and public space management. Their work involves evaluating the disparity between supply and demand for green spaces 🌳, analyzing visual pollution in historical cities 🏙️, and predicting urban waterlogging risks 🌧️. Additionally, they contribute to developing tools to measure public space efficiency and studying the relationship between built environments and social sustainability 🏞️. Their research emphasizes creating better urban environments by addressing ecological concerns, enhancing public spaces, and promoting social well-being through thoughtful urban design.

Publication

His recent publication, “Multihead-Res-SE Residual Network with Attention for Human Activity Recognition” in the journal Electronics, reflects his engagement in research at an advanced level. Co-authoring this paper with established researchers like Hongbo Kang and Chunjie Yang, and contributing to a field as impactful as human activity recognition, highlights his research capabilities.

Conclusion

Mr. Tailong Lv’s solid educational background, innovative research in deep learning, continuous academic excellence, and publication record make him a strong candidate for the Best Researcher Award. His work contributes significantly to the field of AI and human activity recognition, aligning with the qualities expected of an award-winning researcher.