Eduardo Garcia Magraner | Engineering and Technology | Best Researcher Award

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Eduardo Garcia Magraner | Engineering and Technology | Best Researcher Award

Dr Eduardo Garcia, Magraner Ford Motor Company, Spain

🔧 Dr. Eduardo García Magraner is a distinguished expert in industrial automation, manufacturing, and occupational safety. With a Ph.D. in Computer Engineering & Industrial Production (Cum Laude, CEU Cardenal Herrera, 2016) 🎓, he has led key roles at Ford Spain 🚗, from Electromechanical Maintenance to Manufacturing Manager. A Lean Six Sigma Black Belt ⚙️, he has earned multiple innovation and safety awards 🏆, including the Henry Ford Technical Award. A sought-after speaker 🎤 and researcher 📖, his contributions span Industry 4.0, predictive maintenance, and AI-driven efficiency. Passionate about smart factories 🏭, he bridges academia and industry for sustainable progress. 🌍

Publication Profile

Orcid

Academic and Professional Background 

Dr. Eduardo Garcia Magraner 🎓⚙️ is an expert in industrial engineering, automation, and occupational safety. His academic journey began with vocational training in electrical and telecommunications, followed by a Ph.D. in Computer Engineering and Industrial Production (2016) 🏅. Certified in Lean Six Sigma (Black Belt) and occupational risk prevention, he has mastered integrated management systems 🏭✅. With expertise in robotics 🤖, energy efficiency 🌱, and human resources 🤝, he has undertaken extensive additional training in automation and safety. His research explores machine deterioration and throughput optimization 📊. A leader in engineering and innovation, he continuously enhances industry standards 🚀.

Experience

Dr. Eduardo Garcia Magraner has built an impressive career at Ford S.L, starting as a First-Class Electromechanical Maintenance Operator (1990-2001) ⚙️. He advanced to Equipment Engineer (2001-2006) and later became a Maintenance Supervisor (2006) 🔩. His expertise led him to roles such as Senior Equipment Engineer in Maintenance & Automation (2007-2012) and Production Supervisor (2012) 🏭. He progressed to Manufacturing Manager for Body & Stamping (2014) and Champion of M.O.S. (2016) 🔧. As SPOC for Cyber Security (2019) and now Manufacturing Manager for Assembly & Battery Plants (2023), he continues shaping Ford’s production excellence ⚡🚗.

Awards and Recognitions 

Dr. Eduardo Garcia Magraner has been recognized for his outstanding contributions to safety, productivity, and innovation at Ford Spain 🚗🏆. His accolades include multiple Maximum Awards for enhancing press line efficiency (1997, 1999, 2002) and the prestigious Henry Ford Technical Award (2019) for IIoT-based predictive maintenance 🔧📊. He received honors for workplace safety (1995, 2010, 2012) and academic mentorship at the Polytechnic University of Valencia (2014) 🎓👏. His work in AI and cybersecurity earned global recognition (2019, 2020) 🤖🔐. A leader in industrial innovation, he continues to push the boundaries of engineering excellence 🚀⚙️.

Academic Impact 

Dr. Eduardo Garcia is a distinguished researcher in automation and smart manufacturing 🤖🏭. Beyond his groundbreaking research, he has delivered keynote presentations at global conferences, sharing insights on smart factories and AI-driven manufacturing 🔍🎤. His expertise has influenced industry advancements, making him a sought-after speaker in the field. In recognition of his contributions, he was honored with the prestigious CEU Ángel Herrera Prize in 2023 🏆🎓, further solidifying his reputation as a leading researcher. Through his work, Dr. Garcia continues to shape the future of industrial automation, bridging innovation and practical applications for smarter, more efficient production systems ⚙️🌍.

Presentation

Dr. Eduardo García is a distinguished expert in industrial robotics and Industry 4.0 🤖🏭, actively contributing to global conferences and forums. He has delivered impactful presentations at events like EVERii2020, PENTEO2020, and INNOVATION TALKS 2020, addressing smart manufacturing and supply chains 🚀📦. A sought-after speaker, he has shared insights at Advanced Factories, the Global Robot Expo, and the International Conference on Big Data, AI, and IoT 🌍📊. As a Master Professor at PEAKS BUSINESS SCHOOL, he fosters innovation in Industry 4.0. In 2023, he received the prestigious CEU Ángel Herrera Prize for outstanding research excellence 🏆📖.

Research Focus

Dr. Eduardo García Magraner’s research focuses on Industrial Internet of Things (IIoT) 🏭📡, smart manufacturing 🤖, and predictive maintenance 🔧⚙️ within Industry 4.0. His work includes real-time condition monitoring 🕒, virtual sensors 📊, and AI-driven automation 🤖🔍 to enhance efficiency in industrial environments. Key contributions involve sub-bottleneck detection 🚀, autonomous mobile warehouses 🚗🏭, and manufacturing process optimization 📈 using big data and simulation tools 📡💡. His research advances smart factory management 🏭💻, ensuring reliability, reducing downtime, and boosting productivity. His innovations drive next-gen industrial automation 🚀🏗️ for intelligent and self-optimizing manufacturing ecosystems.

Publication Top Notes

I3oT (Industrializable Industrial Internet of Things) Tool for Continuous Improvement in Production Line Efficiency by Means of Sub-Bottleneck Detection Method

Survival 1.0: A Novel Autonomous Industrial Mobile Warehouse (AIMW) for Industrial Environments

Virtual Sensor of Gravity Centres for Real-Time Condition Monitoring of an Industrial Stamping Press in the Automotive Industry

Influence of Mechanical Failures of the Welding Gun on the Magnetic Field Generated in the Measurement of Misalignment

Mini-Sym 4.0. a Novel Simulation Tool to Calculate Real-time Production Line Productivity

Miniterm, a Novel Virtual Sensor for Predictive Maintenance for the Industry 4.0 Era

Manufacturing Maps, a Novel Tool for Smart Factory Management Based on Petri Nets and Big Data Mini-Terms

Shichang Chen | Tech Innovations | Best Researcher Award

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Shichang Chen | Tech Innovations | Best Researcher Award

Dr Shichang Chen, Zhejiang Sci-Tech University, China

Dr. Shichang Chen 🎓🔬 is a distinguished researcher in polymer materials and engineering. He earned his Ph.D. from Zhejiang Sci-Tech University (2017) and completed postdoctoral research at Zhejiang University (2019-2022). Currently, he is a faculty member at Zhejiang Sci-Tech University. His innovations have led to large-scale reactor applications, with 40 invention patents (22 authorized) and transactions exceeding 100 million yuan 💡💰. He has led multiple national and provincial projects and published 40+ papers in top journals 📄📚. Recognized with prestigious awards, including Zhejiang Province’s High-level Talent Support Program (2024), Dr. Chen advances polymer science and engineering globally 🌍.

Publication Profile

Scopus

Education and Experience

Dr. Shichang Chen 🎓 is a dedicated researcher in polymer materials. He earned his Bachelor’s degree in Polymer Materials and Engineering from Yangtze University (2007-2011) 🏛️. He then pursued his Ph.D. in Textile Science and Engineering at Zhejiang Sci-Tech University (2011-2017) 🧵🔬. Following this, he completed a postdoctoral fellowship in Materials Science and Engineering at Zhejiang University (2019-2022) 🏅. Since 2017, he has been contributing to the Department of Polymer Materials at Zhejiang Sci-Tech University 📚🧪. His expertise spans polymer materials, textiles, and advanced material sciences, driving innovation in the field 🚀.

Research Funding & Projects

Dr. Shichang Chen 🎓🔬 has successfully secured and led multiple prestigious research projects, showcasing his expertise in scientific innovation. His achievements include securing 2 National Funds 🇨🇳, 2 Zhejiang Provincial Funds 🏅, and 10 Enterprise Projects 💼. He has actively contributed to key national research initiatives, including the 973 Program 🔍, National Key R&D Programs 🧪, and three strategic consulting research projects at the Chinese Academy of Engineering 🏛️. Dr. Chen’s dedication to advancing research and technological development continues to make a significant impact in his field. 🚀📚

Research Achievements 

Dr. Shichang Chen has made remarkable contributions to reactor applications for 10,000-ton and 1,000-ton production lines ⚙️🏭. He has declared 40 invention patents, with 22 authorized, and patent transactions exceeding 100 million yuan 💡💰. As a lead researcher, he has hosted 2 national funds, 2 Zhejiang Provincial funds, and 10 enterprise projects, while also playing a key role in national 973 and strategic consulting research projects 📊🔬. With a strong academic presence, he has published a book and 40 papers in top-tier journals like Macromolecules, focusing on polymers and chemical engineering 📖🧪.

Honor Award 

Dr. Shichang Chen 🎓 is a distinguished researcher recognized for his contributions to textile science. In April 2024, he was selected for the Zhejiang Province High-level Talent Support Program as a young top talent 🌟. The previous month, he joined the Zhejiang Academician Pair Young Talents Program 🏅. His excellence was also acknowledged in October 2021 when he was awarded the China Association for Science and Technology Youth Lifting Talent Project 🚀. Additionally, he serves as a Young Editorial Member for the EI Journal of Textile Research (December 2021) and Modern Textile Technology (January 2023) 📖🔬.

Research Focus

Dr. Shichang Chen’s research focuses on polymer engineering, mooring rope mechanics, and chemical process simulations 🔬⚙️. His work includes dynamic stiffness analysis of damaged polyester mooring ropes 🛳️, the mechanical behavior of aramid and polyester fibers under loading history ⚡, and falling film polymerization processes 🏭. He also explores numerical simulation of variable viscosity fluids 💻🔄 and waste PET depolymerization for recycling ♻️🧪. His studies contribute to marine engineering, textile chemistry, and sustainable polymer recycling, advancing both industrial applications and environmental sustainability 🌍🔄. His expertise spans mechanics, materials science, and chemical engineering 🏗️⚗️.

Publication Top Notes

Dynamic stiffness of full-scale damaged polyester mooring ropes

Effects of bedding-in loading history on mechanical behaviors of aramid HMPE and polyester mooring ropes

Process Simulation of falling film liquid-state polymerization of polyester

Numerical Simulation Strategy and Applications for Falling Film Flow with Variable Viscosity Fluids

Depolymerization of waste poly(ethylene terephthalate) into bis(2-hydroxyethyl) terephthalate: Catalytic glycolysis mechanism and kinetics

Mona AbouEleaz | Engineering and Technology | Best Researcher Award

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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

 

Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

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Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Kaimin Wei, Jinan University, China

Kaimin Wei is a full professor at the College of Information Science and Technology, Jinan University, China 🇨🇳. He earned his Ph.D. in Computer Science from Beihang University (2015), Master’s in Computer Application Technology from Zhengzhou University (2010), and Bachelor’s in Computer Science from Yuncheng University (2007) 🎓. A distinguished Young Pearl River Scholar 🌟, his research focuses on mobile computing, edge intelligence, and AI security 📱🤖🔒. Prof. Wei has published extensively in top journals and conferences, contributing to advancements in algorithm optimization and security techniques 📊📚.

Publication Profile

Orcid

Academic Background 

Prof. Kaimin Wei 🌟 holds a Ph.D. in Computer Science from Beihang University (2015) 🎓, a Master’s degree from Zhengzhou University (2010) 📚, and a Bachelor’s from Yuncheng University (2007) 🎯. His academic journey showcases dedication and excellence in the field of computer science 💻. Recognized for his outstanding achievements, he was honored as a Young Pearl River Scholar 🌊, reflecting his leadership potential and scholarly impact. Prof. Wei’s contributions to academia continue to inspire, highlighting his commitment to research, innovation, and education 🚀

Research Interests 

Prof. Kaimin Wei is a distinguished expert in Mobile Computing 📱, specializing in Edge Intelligence 🌐 and Artificial Intelligence Security 🔐. His research focuses on enhancing the efficiency and security of mobile technologies, leveraging cutting-edge edge intelligence to optimize data processing and real-time decision-making. Prof. Wei’s work in AI security ensures robust protection against emerging cyber threats, contributing to the development of safer, smarter digital ecosystems. His innovative approach bridges the gap between mobile computing and advanced AI applications, driving technological progress and shaping the future of secure, intelligent systems. 🚀🤖

Research Focus

Prof. Kaimin Wei’s research focuses on privacy-preserving technologies, federated learning, mobile crowdsensing, and cybersecurity 🔐📡. His work explores UAV crowdsensing with energy efficiency, gradient inversion attacks in federated learning without prior knowledge, and group task recommendations using neural collaborative approaches 🤖✨. He also investigates secure device pairing through acceleration-based methods with visual tracking and develops robust defense mechanisms against adversarial attacks using feature purification networks 🛡️📊. Prof. Wei’s interdisciplinary research blends Internet of Things (IoT), machine learning, and security protocols to enhance data privacy and system resilience 🌍🔍.

Publication Top Notes

PD-DRL: Towards privacy-preserving and energy-sustainable UAV crowdsensing

GI-SMN: Gradient Inversion Attack Against Federated Learning Without Prior Knowledge

Group Task Recommendation in Mobile Crowdsensing: An Attention-Based Neural Collaborative Approach

Attacks on Acceleration-Based Secure Device Pairing With Automatic Visual Tracking

FePN: A robust feature purification network to defend against adversarial examples

A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities

Automatic Tagging by Leveraging Visual and Annotated Features in Social Media