Efendi Nasibov | Computer Science | Research Excellence Award

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Prof. Dr. Efendi Nasibov | Computer Science | Research Excellence Award

Dokuz Eylul University | Turkey

Prof. Dr. Efendi Nasiboğlu is a researcher in Computer Sciences at Dokuz Eylül University, İzmir, Turkey. He has authored over 107 scholarly publications indexed in Scopus and Web of Science, accumulating more than 1,101 citations with an h-index of 16. His research expertise spans fuzzy systems, regression modeling, computational intelligence, machine learning, and applied data analysis, with contributions to both theoretical foundations and real-world applications in engineering, manufacturing, healthcare, and smart systems. Dr. Nasiboğlu actively collaborates with international researchers and has published in reputable journals and conferences, contributing to methodological advancements with measurable societal and technological impact.

 

Citation Metrics (Scopus)

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Citations
1,101

Documents
107

h-index
16

🟦 Citations 🟥 Documents 🟩 h-index

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             View Google Scholar Profile

Featured Publications


On the nearest parametric approximation of a fuzzy number

Fuzzy Sets and Systems  (2008). Citations: 107

A new unsupervised approach for fuzzy clustering

– Fuzzy Sets and Systems. (2007). Citations : 91

Public transport route planning: Modified Dijkstra’s algorithm

– International Conference on Computer Science and Engineering. (2017). Citations :  76

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

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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 Assistant Professor of Computer Engineering at the University of Tabuk, Saudi Arabia, whose research focuses on the intersection of energy-efficient communication networks, machine learning, and distributed systems. His work advances intelligent computing architectures that optimize performance, reduce energy consumption, and enable sustainability in next-generation networks. Dr. Alenazi has contributed to several impactful studies, including energy-efficient neural network embedding in IoT over passive optical networks, distributed machine learning in cloud–fog environments, and AI-driven frameworks for 6G-IoT-based remote cardiac monitoring. His research extends to federated learning for low-latency IoT communications, hybrid cloud edge architectures for real-time cryptocurrency forecasting with blockchain integration, and machine learning-optimized energy management for resilient residential microgrids with electric vehicle integration. His scholarly output, cited over 50 times with an h-index of 4 and i10-index of 3, reflects growing recognition in the domains of sustainable networking and intelligent systems. Dr. Alenazi’s work combines AI, IoT, and cloud–fog computing to create adaptive, energy-aware solutions for smart environments, healthcare, and industrial systems. Through his innovative contributions, he continues to enhance the efficiency, reliability, and intelligence of modern communication infrastructures, positioning his research at the forefront of AI-powered green networking and distributed intelligence for the evolving digital ecosystem.

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. Cited By : 13

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. Cited By : 12

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. Cited By : 10

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. Cited By : 6

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. Cited By : 4

Dr Santanu Roy | Computer Vision | Best Researcher Award

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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 🎓

  • Ph.D. in Medical Image Processing
    NITK Surathkal, India (July 2016 – 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 – June 2011)
  • B.Tech in Electronics and Communication Engineering
    St. Thomas College of Engineering and Technology, WBUT Kolkata, India (June 2004 – May 2008)
    Percentage: 77.71%

Experience 💼

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 🔍

Dr. Roy’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 🏆

  • Best Paper Presentation Award at the 15th International Conference on Machine Vision (ICMV’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 📚

  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.