Mohammed M Alenazi | Computer Science and Artificial Intelligence | Best Researcher Award

Dr. Mohammed M Alenazi | Computer Science and Artificial Intelligence | Best Researcher Award

Assistance Professor | University of Tabuk | Saudi Arabia

Dr. Mohammed M. Alenazi is an accomplished researcher and academic specializing in Artificial Intelligence, Machine Learning, and Energy Optimization in IoT Networks. He holds a PhD in Electrical and Electronics Engineering from the University of Leeds, a Master of Engineering in Computer Engineering from the Florida Institute of Technology, a Bachelor of Engineering in Computer Engineering from Prince Fahd Bin Sultan University, and an Associate Degree in Electrical/Electronics Equipment Installation and Repair from Tabuk College of Technology. He began his professional career as a Senior Engineer at Saudi Telecom Company, gaining extensive experience in optical fiber networks and large-scale communication systems, and later transitioned into academia as a Teaching Assistant at Northern Border University and the University of Tabuk, where he currently serves as an Assistant Professor. His research interests focus on energy-efficient deployment of ML-based services in IoT networks, neural network embedding in passive optical networks, and AI-driven intelligent systems, including a patented vehicle safety communication system. Dr. Alenazi has published in reputed journals and conferences including IEEE Xplore and ResearchGate and actively participates in professional organizations such as IEEE, AAAI, AISB, the Saudi Council of Engineers, and the Project Management Institute, holding certifications including CCNA, CompTIA Security+, and PMP. He has received awards and honors for his contributions to AI and networking research, and his skills include machine learning, energy optimization, teaching, and project management. His research has received 28 citations across 8 documents, with an h-index of 3, reflecting his growing academic impact and influence in the field.

Profiles : ORCID | Scopus | Google Scholar | ResearchGate

Featured Publications

1. Alenazi, M. M., Yosuf, B. A., El-Gorashi, T., & Elmirghani, J. M. H. (2020). Energy efficient neural network embedding in IoT over passive optical networks.

2.Yosuf, B. A., Mohamed, S. H., Alenazi, M. M., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2021). Energy-efficient AI over a virtualized cloud fog network.

3.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.

4.Banga, A. S., Alenazi, M. M., Innab, N., Alohali, M., Alhomayani, F. M., Algarni, M. H., et al. (2024). Remote cardiac system monitoring using 6G-IoT communication and deep learning.

5.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.

Dr Santanu Roy | Computer Vision | Best Researcher Award

Dr Santanu Roy | Computer Vision | Best Researcher Award

Assistant Professor at Pandit Deendayal Energy University , India

Dr. Santanu Roy is a dedicated researcher and educator specializing in medical image processing and computer vision. With a Ph.D. from NITK Surathkal, he has developed innovative algorithms for cancer detection using deep learning techniques. His passion for advancing healthcare through technology is reflected in his extensive research publications and teaching experience across various esteemed institutions.

Profile

Education Qualification ๐ŸŽ“

  • Ph.D. in Medical Image Processing
    NITK Surathkal, India (July 2016 โ€“ August 2021)
    Thesis: Algorithms for Color Normalization and Nuclei Segmentation of Liver Cancer Histopathology Images
    CPI: 9.00/10.0
  • M.Tech in Information and Communication Technology
    Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT), Gandhinagar, India (July 2009 โ€“ June 2011)
  • B.Tech in Electronics and Communication Engineering
    St. Thomas College of Engineering and Technology, WBUT Kolkata, India (June 2004 โ€“ May 2008)
    Percentage: 77.71%

Experience ๐Ÿ’ผ

Dr. Roy has held various academic positions, including Assistant Professor in the CSE Department at NIIT University (Sept 2023 – July 2024) and Christ (Deemed to be University) (Oct 2022 – Sept 2023). He also served as a Teaching Assistant at NITK Surathkal, contributing to projects in liver cancer diagnosis. His teaching experience spans subjects like deep learning, machine learning, and digital image processing.

Research Interest ๐Ÿ”

Dr. Royโ€™s research interests focus on medical image processing, computer vision, and image classification using deep learning. He is particularly dedicated to enhancing diagnostic techniques in healthcare through innovative computational methods.

Upcoming Projects

  1. AI-Driven Diagnostic Tools: Building on his work with liver cancer histopathology images, Dr. Roy aims to develop AI tools that can assist in real-time diagnosis across various medical imaging modalities.
  2. Telemedicine Solutions: A project aimed at leveraging computer vision technologies to enhance telemedicine services, making healthcare more accessible, especially in rural areas.
  3. Virtual Lab Expansion: Dr. Roy plans to expand the Virtual Lab initiative, enhancing its offerings and providing more students with opportunities to engage in impactful AI research.

Awards and Achievements ๐Ÿ†

  • Best Paper Presentation Award at the 15th International Conference on Machine Vision (ICMVโ€™2022), Rome, Italy (2023).
  • Full-time Ph.D. Scholarship from NITK Surathkal (2016-2021).
  • GATE EC 2009: All India Rank 2883.
  • GATE EC 2008: All India Rank 4885.

Publications ๐Ÿ“š

  1. Attention-based VGG-Lite Model and Novel Pooling Technique for Pneumonia and Covid-19 Detection from Imbalanced CXR Dataset
    IEEE Transactions on Emerging Topics in Computational Intelligence (2023)

    • Under minor revision.
  2. SVD-CLAHE Boosting and Balanced Loss Function for Covid-19 Detection from an Imbalanced Chest X-Ray Dataset
    Computers in Biology and Medicine (2022)
  3. Novel Edge Detection Technique for Nuclei Segmentation of Liver Cancer Histopathology Images
    Journal of Ambient Intelligence and Humanized Computing (2023)
  4. Mathematical Analysis of Histogram Equalization Techniques for Medical Image Enhancement
    Multimedia Tools and Applications (2024)
  5. A Novel Color Normalization Method for Hematoxylin and Eosin Stained Histopathology Images
    IEEE Access (2019)

    • Google Citations: 31.
  6. A Study About Color Normalization Methods for Histopathology Images
    Micron (2018)

    • Google Citations: 160.