Dr. Mohammed Alenazi | Cloud Edge | Best Researcher Award

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Dr. Mohammed Alenazi | Cloud Edge | Best Researcher Award 

Dr. Mohammed Alenazi | Cloud Edge | University of Tabuk | Saudi Arabia

Dr. Mohammed Alenazi is an accomplished academic and researcher with a strong background in Electrical and Electronics Engineering, focusing on energy-efficient artificial intelligence (AI), Internet of Things (IoT), and machine learning-based network optimization. He holds a Doctor of Philosophy (Ph.D.) in Electrical and Electronics Engineering from the University of Leeds, United Kingdom, a Master of Engineering in Computer Engineering from Florida Institute of Technology, and a Bachelor of Engineering in Computer Engineering from University Sultan Bin Fahad. His academic journey is further complemented by an Associate’s degree in Electrical and Electronics Equipment Installation and Repair from Tabuk College of Technology. Professionally, Dr. Mohammed Alenazi has accumulated extensive experience through his roles as a Senior Engineer at Saudi Telecom Company, where he contributed to the development of advanced optical fiber communication systems, and as a Teacher Assistant at Northern Border University and later the University of Tabuk, where he has been instrumental in guiding research and teaching in electrical and computer engineering disciplines. His scholarly productivity includes 8 publications, 28 citations, and an h-index of 3, reflecting a growing impact in data-driven intelligent systems.

Professional Profile: ORCID | Scopus | Google Scholar

Selected Publications

  1. Alenazi, M. M., Yosuf, B. A., Mohamed, S. H., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2022). Energy Efficient Placement of ML-Based Services in IoT Networks. IEEE International Mediterranean Conference on Communications and Networking. (4 citations)

  2. Alenazi, M. M., Yosuf, B. A., Mohamed, S. H., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2021). Energy-Efficient Distributed Machine Learning in Cloud Fog Networks. IEEE 7th World Forum on Internet of Things (WF-IoT). (9 citations)

  3. Alenazi, M. M., Yosuf, B. A., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2020). Energy Efficient Neural Network Embedding in IoT over Passive Optical Networks. IEEE International Conference on Transparent Optical Networks (ICTON). (13 citations)

  4. Alenazi, M. M., Banga, A. S., Innab, N., Alohali, M., Alhomayani, F. M., & Algarni, M. H. (2024). Remote Cardiac System Monitoring Using 6G-IoT Communication and Deep Learning. Wireless Personal Communications, 136(1), 123–142. (5 citations)

  5. Alenazi, M. M. (2024). IoT and Energy. In Internet of Things—New Insights. (3 citations)

Dr. S M Salahuddin Morsalin | Edge Computing Awards | Young Scientist Award – 5450

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Dr. S M Salahuddin Morsalin | Edge Computing Awards | Young Scientist Award 

Dr. S M Salahuddin Morsalin, National Yunlin University of Science and Technology, Taiwan

S M Salahuddin Morsalin is an accomplished Electronic Engineer with over three years of professional experience in designing, developing, and testing electronic systems, coupled with significant academic teaching contributions. He is currently an Adjunct Lecturer at the Department of Electronic Engineering, National Yunlin University of Science and Technology, Taiwan, where he teaches advanced courses such as Embedded System Design for AI IoT and AI Chip Design. In addition to his academic role, he serves as a Senior Engineer at Foxconn Technology Group, Taiwan, where he focuses on high-speed signal applications, cloud solutions, and advanced automotive systems. Previously, Salahuddin worked as a Researcher at the Big Data Research Center, National Yunlin University, conducting research on electrical machines and edge computing, contributing to publications, and mentoring students. His industry expertise includes a role as an Electrical Hardware Design Engineer at Wiwynn Corporation, Taiwan, where he specialized in cloud system design and hardware troubleshooting for AMD and Intel platforms. Salahuddin’s teaching journey began at Nanhua University, Taiwan, as a Lecturer and Teaching Assistant in Computer Science, delivering courses on Digital Systems, Neural Networks, and Pattern Recognition.

Professional Profile:

ORCID

Summary of Suitability for the Young Scientist Award: S M Salahuddin Morsalin

S M Salahuddin Morsalin is a highly deserving candidate for the Young Scientist Award, given his impressive academic background, innovative research contributions, and commitment to teaching in the field of electronic engineering. His work exemplifies the qualities of a young scientist who is making significant strides in technology and education.

🎓 Education 

  1. M.Sc. in Electronic Engineering
    📍 National Yunlin University of Science & Technology, Taiwan
    🗓️ Year: 2021

    • Specialization: AI Internet of Things and Embedded Systems
  2. B.Sc. in Electrical and Electronic Engineering
    📍 International University, Bangladesh
    🗓️ Year: 2016

👨‍💼  Work Experience

  1. Adjunct Lecturer (February 2024 – Present)
    📍 Department of Electronic Engineering, National Yunlin University of Science & Technology, Taiwan
    🎓 Key Courses Taught:

    • 🤖 Embedded System Design for AI Internet of Things
    • 🧠 AI Chip Design and System Analysis
    • ⏱️ Real-Time Embedded Application Development
  1. Senior Engineer (September 2023 – Present)
    🏢 R&D and Engineering Division, Foxconn Technology Group, Taiwan
    🔧 Key Responsibilities:

    • 🔍 Requirement analysis for cloud and edge computing solutions.
    • 📡 Development of high-speed signal processing applications.
    • 🛠️ Industrial internet system design for cloud platforms.
    • 🚗 Development of automotive solutions for advanced signal systems.
    • 🧪 System verification using test instruments.
  1. Researcher (March 2023 – September 2024)
    📍 Big Data Research Center, National Yunlin University of Science & Technology, Taiwan
    🔬 Key Responsibilities:

    • ⚙️ Conducted edge computing and electrical machine research.
    • 📊 Data analysis, literature review, and result publications.
    • 📝 Presented findings at seminars and collaborated on research projects.
    • 🎓 Mentored students and managed lab equipment maintenance.

🏆 Achievements & Awards

  • 🏅 Outstanding Research Contribution Award – National Yunlin University of Science & Technology (2023)
  • 📜 Research Publications: Multiple papers published in peer-reviewed journals and conferences in edge computing and embedded systems.
  • 🏆 Recognition for Excellence in Teaching – Nanhua University, Taiwan (2021).
  • 🧠 Innovative Embedded Design Project Award at Foxconn Technology Group (2023).

🌟 Key Skills & Expertise

  • 🤖 Embedded System Design for AI and IoT
  • 🌐 Cloud & Edge Computing Solutions
  • 🔧 High-Speed Signal Processing Systems
  • 📊 Data Analysis & Research Publication
  • 🎓 Academic Teaching & Student Mentoring

Publication Top Notes:

Improvement of Human Pose Estimation and Processing With the Intensive Feature Consistency Network

FHI-Unet: Faster Heterogeneous Images Semantic Segmentation Design and Edge AI Implementation for Visible and Thermal Images Processing

FIBS-Unet: Feature Integration and Block Smoothing Network for Single Image Dehazing

FGSC: Fuzzy Guided Scale Choice SSD Model for Edge AI Design on Real-Time Vehicle Detection and Class Counting

A 0.3 V PNN Based 10T SRAM with Pulse Control Based Read-Assist and Write Data-Aware Schemes for Low Power Applications

Dr. Junaid Shuja | Edge Computing Awards | Top Researcher Awards

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Dr. Junaid Shuja | Edge Computing Awards | Top Researcher Awards

Dr. Junaid Shuja ,Southeast Missouri University,United States

Dr. Junaid Shuja is a Senior Lecturer and Cisco Certified CCNA Instructor at Universiti Teknologi PETRONAS, Malaysia, with over 8 years of teaching experience. He holds a Ph.D. in Computer Science from the University of Malaya, where he completed his dissertation on mobile cloud computing. Dr. Shuja has taught a wide range of courses, including advanced algorithms and cloud computing, and has published over 70 research articles with a notable H-index of 30. His research focuses on machine learning applications in edge networks. He has secured multiple research grants, including projects on data visualization, ML, and cultural heritage preservation. Recognized as a top 2% researcher by Stanford in 2023, he has also received several awards for his research contributions and serves on the editorial boards of prominent journals.

Professional Profile:

Scopus

Suitability Summary for Dr. Junaid Shuja for the Top Researcher Award

Dr. Junaid Shuja stands out as an exceptional candidate for the Top Researcher Award due to his distinguished contributions and achievements in the field of Computer and Information Sciences. His extensive qualifications and accomplishments highlight his suitability for this recognition

🎓Education:

Dr. Junaid Shuja earned his Ph.D. in Computer Science with a focus on Distributed Systems and Mobile Cloud from the University of Malaya, Malaysia, from October 2013 to January 2017. His dissertation, titled “Integrated Vector Instruction Translator and Offloading Framework for Mobile Cloud Computing,” was completed with distinction and earned him the “Graduate on Time” award. He holds an MS in Computer Science from COMSATS Institute of Information Technology, Pakistan, where he studied from September 2010 to May 2012, achieving a CGPA of 3.72/4.0 with a focus on energy-efficient designs for data center networks. His academic journey began with a BS in Computer and Information Sciences from the Pakistan Institute of Engineering and Applied Sciences, Pakistan, completed between October 2005 and July 2009, where he focused on application development, database design, information systems, and computer networks, graduating with a CGPA of 3.12/4.0.

🏢Work Experience:

Dr. Junaid Shuja is currently serving as a Senior Lecturer and Assistant Professor at Universiti Teknologi PETRONAS, Malaysia, since March 2023. His role involves teaching, research supervision, grant acquisition, and commercialization, with a focus on machine learning applications in edge networks. Prior to this, he was an Associate Professor at FAST-NUCES, Karachi, from August 2022 to January 2023, where he taught AWS cloud computing and advanced algorithms and supervised six postgraduate students. From April 2017 to July 2022, Dr. Shuja was an Assistant Professor (Tenure Track) at COMSATS Islamabad, handling undergraduate and graduate teaching, project supervision, and administrative duties. He also worked as a Post-Doctoral Fellow at Umm al-Qura University, Saudi Arabia, from February 2020 to December 2020, where he developed research proposals and secured funding for COVID-19 contact tracing applications. Earlier in his career, he was a Research Assistant at the University of Malaya, Malaysia, from October 2013 to September 2016, supporting research under the BrightSpark Program. He also held positions as a Lecturer and Research Associate at CIIT Abbottabad, Pakistan, and as an Information Security Analyst at NIMIS, Islamabad. Additionally, he worked as a Freelance Web Developer on Odesk from August 2009 to January 2013.

🏆Awards and Recognitions:

Dr. Junaid Shuja has been recognized as one of the top 2% research scientists according to the Stanford Study in 2023. He has also received the Best and Young Researcher Awards from COMSATS University, acknowledging his outstanding contributions to the field. Additionally, he was honored with the Best Paper Award at an international conference, highlighting the impact and quality of his research

Publication Top Notes:

  • Microservices Enabled Bidirectional Fault-Tolerance Scheme for Healthcare Internet of Things
  • Deep Neural Networks Meet Computation Offloading in Mobile Edge Networks: Applications, Taxonomy, and Open Issues
  • Multi-Objective Task-Aware Offloading and Scheduling Framework for Internet of Things Logistics
  • Federated Learning for Digital Twin-Based Vehicular Networks: Architecture and Challenges
  • An Efficient Approach for Tampering Attack Detection in WSN Using Blockchain