Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award

Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award 

Assoc. Prof. Dr. Waleed Mahmoud Elsayed, Beni-suef university, Saudi Arabia

Dr. Waleed Mahmoud Ead is an accomplished Assistant Professor in the Faculty of Computing and Information at Al-Baha University, Saudi Arabia, with over 15 years of experience in digital business transformation, data science, and applied research. He holds a Ph.D. in Computers and Informatics from Menoufia University, Egypt, where he focused on privacy-preserving techniques in social networks. Throughout his career, Dr. Ead has developed expertise in business intelligence, data mining, machine learning, cloud computing, and big data analytics, and he is SAS-certified in multiple disciplines, including machine learning and visual analytics. His research interests span social network analysis, distributed databases, precision medicine, and cybersecurity. He has served in various academic roles across prominent Egyptian institutions and has co-supervised doctoral and master’s research in genetics, AI, and privacy in healthcare. A dedicated peer reviewer for renowned journals such as Springer Nature and Inderscience, Dr. Ead is also an active contributor to academic conferences and international workshops. Beyond academia, he is a technology enabler, STEM judge, and entrepreneur, with projects focused on sustainable agriculture and digital innovation.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award: Dr. Waleed Mahmoud Ead

Dr. Waleed Mahmoud Ead is highly suitable for the Best Researcher Award, given his exceptional combination of research depth, academic leadership, interdisciplinary engagement, and societal impact. His qualifications are supported by the following key strengths

🎓 Education

  • 🥇 2004: B.Sc. (Honor) in Information and Technology Systems – Zagazig University, Egypt

  • 📚 2012: M.Sc. in Computers and Informatics – Menoufia University, Egypt
      📘 Thesis: “Developing an Intelligent Technique in Web Mining”

  • 🎓 2018: Ph.D. in Computers and Informatics – Menoufia University, Egypt
      📗 Thesis: “Privacy Preserving in Social Networks”

👨‍🏫 Academic Work Experience

  • 🇸🇦 2024–Present: Assistant Professor, Faculty of Computing and Information – Al-Baha University, Saudi Arabia

  • 🇪🇬 2022–2023: Assistant Professor, CSIT – Egypt-Japan University of Science and Technology

  • 🇪🇬 2018–2022: Assistant Professor, Faculty of Computers & AI – Beni-Suef University

  • 🇪🇬 2015–2018: Lecturer Associate, Faculty of Information Technology – MUST University

  • 🇪🇬 2014: Lecturer Associate, Faculty of Computers & Information – Beni-Suef University

  • 🇪🇬 2012: Lecturer Associate, CSC – October 6 University

  • 🇪🇬 2006–2012: Teaching Assistant, CSC – October 6 University

🏆 Achievements & Honors

  • 🧠 SAS Certified: Machine Learning, Visual Analytics, Business Planning

  • 💡 Developed systems for international conferences

  • 🌍 Peer Reviewer for top journals & publishers (Inderscience, Springer, EAI, etc.)

  • 🧬 Co-supervisor for Ph.D. and Master’s students in AI, bioinformatics, and precision medicine

  • 🥇 Honor degree in B.Sc.

  • 👩‍⚖ STEM Judge: INTEL ISEF & Graduation Projects

  • 💼 Speaker and participant in events by DAAD, UNESCO, Microsoft, SAS, Oracle

  • 🌱 Founder of IGreen (Intelligent Adaptive Environmental Farm)

  • 🚀 Participated in entrepreneurship programs (Start Egypt, Flat6Labs)

  • 🧭 Bridging analytics and IT knowledge for social development

Publication Top Notes:

An Optimized Hierarchal Cluster Formation Approach for Management of Smart Cities

ODCS: On-Demand Hierarchical Consistent Synchronization Approach for the IoT

A General Cyber Hygiene Approach for Financial Analytical Environment

Feedforward Deep Learning Optimizer-based RNA-Seq Women’s cancers Detection with a hybrid Classification Models for Biomarker Discovery

Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder

Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms

Prof. Arturo Benayas Ayuso | Smart Automation Awards | Best Researcher Award

Prof. Arturo Benayas Ayuso | Smart Automation Awards | Best Researcher Award 

Prof. Arturo Benayas Ayuso, Universidad Politécnica de Madrid, Spain

Arturo Benayas Ayuso, born in April 1976, is a highly skilled Naval Architect with a Master’s degree from the Universidad Politécnica de Madrid and is currently pursuing a Ph.D. in Naval Architecture. His Ph.D. research focuses on applying IoT to ship design, shipbuilding, manufacturing, and management. Arturo has extensive professional experience in the naval industry, currently serving as Integration Lead for the “El Cano” platform at NAVANTIA, where he oversees the integration of industry 4.0 technologies in naval shipbuilding. He has previously worked as a FORAN-PLM Technical Account Manager and Solution Architect Associate Manager, leading integration projects for the Spanish Navy, including the S80 submarine program. Fluent in Spanish, English, French, and Portuguese, Arturo has contributed to several conferences, authored publications in shipbuilding and IoT, and co-authored a book chapter on IoT cybersecurity.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: Arturo Benayas Ayuso

Professional Background: Arturo Benayas Ayuso has extensive experience in naval architecture, ship design, and industry 4.0 technologies. His expertise spans over two decades, with a strong focus on integrating IoT and PLM (Product Lifecycle Management) systems into naval shipbuilding. As the Platform Integration Lead at NAVANTIA and his previous roles, he has successfully led digitization projects, coordinated large development teams, and managed multi-shipyard collaborations with notable defense projects like the Spanish Navy’s S80 submarine and Royal Navy’s CVF project.

Education:

  • MSc Naval Architect – Universidad Politécnica de Madrid, 2005 (Marine motors specialist).
  • PhD (On-going) – Naval Architect PhD Researcher focusing on “IoT applied to Ship Design, Shipbuilding, Manufacturing, and Ship Management.”

Work Experience:

  1. 2020–Present: Accenture – Tecnilógica
    • Position: PLM Associate Manager, Platform Integration Lead (Naval shipbuilding).
    • Responsibilities:
      • Lead the integration of the “El Cano” platform at NAVANTIA, a platform that incorporates Industry 4.0 principles into naval shipbuilding.
      • Manage a fixed team of 7 members and up to 10 floating members.
      • Define and deploy OOTB software solutions, and create custom requirements for the Spanish Navy’s digitization efforts using Siemens CAD-CAM-CAE-PLM systems.
      • Prepare project tenders, including the economic assessments.
      • Apply Agile methodologies to ensure timely project delivery.
  2. 2005–2020: SENER, Ingeniería y Sistemas, S.A. (Naval Systems Section)
    • Position: Solution Architect Associate Manager / FORAN-PLM Technical Account Manager.
    • Responsibilities:
      • Managed and coordinated the integration of FORAN with Windchill and Teamcenter PLM systems.
      • Supervised integration for key naval projects such as the S80 Submarine Program for the Spanish Navy, BAM Naval Project, and collaborations with Aker Offshore Platform and Royal Navy’s CVF Program.
      • Directed development teams and maintained a neutral integration approach between FORAN and PLM platforms.
      • Led the migration of the Spanish S80P submarine to the new FORAN version and integrated Windchill PLM.
  3. 2003–2004: Infomarine & Infopower Magazines (Internship)
    • Responsibilities:
      • Wrote articles and advertisements for magazines.
      • Improved internal databases and created a new database for InfoEnviro magazine.

Publication top Notes:

Internet of Things Cybersecurity: Blockchain as First Securitisation Layer of an IoT Network

Data management for smart ship or how to reduce machine learning cost in IoS applications

Automated/controlled storage for an efficient mbom process in the shipbuilding managing the iot technology