Dr. vincebt majanga | Artificial intelligence | Best Researcher Award

Posted on by Computer Scientists Awards

Dr. vincebt majanga | Artificial intelligence | Best Researcher Award

Post doctoral research fellow, university of south africa, South Africa.

Dr. Vincent Idah Majanga  is a dynamic and passionate researcher in Artificial Intelligence (AI), with over a decade of impactful experience in developing cutting-edge algorithms to solve complex real-world problems. His primary expertise lies in machine learning, deep learning, neural network optimization, and computer vision—especially for medical imaging and diagnostic tasks. Dr. Majanga is proficient in Python and Java, and his interdisciplinary skills extend to computer-aided diagnostics, simulation and modeling, computer forensics, and networking. A devoted academician and mentor, he has served in teaching and research capacities across renowned institutions in Kenya and South Africa. His current role as a Postdoctoral Researcher at the University of South Africa (UNISA) underlines his continued contributions to AI-driven healthcare solutions and intelligent systems.

Publication Profile

ORCID

📘 Education Background

Dr. Majanga completed his Ph.D. in Computer Science from the University of KwaZulu-Natal  (2018–2022), focusing on dental image segmentation and AI-based diagnostic systems. He holds an MSc in Computer Science from the University of Nairobi (2012–2014), and a BSc in Computer Science (Upper Second Class) from Kabarak University  (2009–2011). He also studied Computer Engineering at Moi University (2005–2008, credit transferred), and attended Nairobi School for his secondary education (2001–2004). His academic foundation forms the bedrock of his AI-driven research innovations.

💼 Professional Experience

Dr. Majanga is currently a Postdoctoral Researcher at UNISA  (Dec 2023–Present), where he works on deep learning, neural networks, transfer learning, and model optimization in image processing. He is also a part-time lecturer at Masinde Muliro University of Science and Technology  since 2022. Previously, he served as an Assistant Lecturer at Laikipia University  (2015–2023), contributing to curriculum development and student supervision. He has also lectured part-time at JKUAT Nakuru Campus, Dedan Kimathi University, and Kabarak University. Across these roles, he has consistently contributed to high-impact teaching, curriculum development, and academic mentorship.

🏆 Awards and Honors

Dr. Majanga has earned recognition through certifications in Research Ethics from the Clinical Trials Centre at The University of Hong Kong 🏅, completing three modules between March and April 2024—Introduction to Research Ethics, Research Ethics Evaluation, and Informed Consent. These certifications affirm his commitment to ethical research standards and responsible conduct in AI healthcare studies.

🔬 Research Focus

Dr. Majanga’s research focuses on Artificial Intelligence applications in medical imaging and diagnostics, with a specialization in deep learning, computer vision, and unsupervised segmentation. His significant contributions include blob detection and component analysis techniques for identifying cancerous lesions and dental caries in radiographs. His Ph.D. research and publications highlight strong applications of active contour models, connected component analysis, and dropout regularization in healthcare AI systems.

📝 Conclusion

Dr. Vincent Idah Majanga is a dedicated AI researcher and academician with a rich educational and professional background that aligns with transformative applications of artificial intelligence in medical diagnostics. His teaching, ethical research approach, and cross-continental academic presence have made him a valuable contributor to the global AI and computer science communities.

📚 Top Publications Highlights

  1. Automatic Blob Detection Method for Cancerous Lesions in Unsupervised Breast Histology Images
    📅 2025 | 📰 Bioengineering, 12(4), p.364
    🔎 Cited by: 8 articles

  2. Active Contours Connected Component Analysis Segmentation Method of Cancerous Lesions in Unsupervised Breast Histology Images
    📅 2025 | 📰 Bioengineering, 12(6), p.642
    🔎 Cited by: 5 articles

  3. A Survey of Dental Caries Segmentation and Detection Techniques
    📅 2022 | 📰 The Scientific World Journal, 2022
    🔎 Cited by: 21 articles

  4. Automatic Blob Detection for Dental Caries
    📅 2021 | 📰 Applied Sciences, 11(19), p.9232
    🔎 Cited by: 17 articles

  5. Dental Images’ Segmentation Using Threshold Connected Component Analysis
    📅 2021 | 📰 Computational Intelligence and Neuroscience, 2021
    🔎 Cited by: 12 articles

  6. Dropout Regularization for Automatic Segmented Dental Images
    📅 2021 | 📰 Asian Conference on Intelligent Information and Database Systems, Springer
    🔎 Cited by: 6 articles

  7. A Deep Learning Approach for Automatic Segmentation of Dental Images
    📅 2019 | 📰 MIKE 2019, Springer
    🔎 Cited by: 18 articles

  8. Component Analysis
    📅 2025 | 📰 WIDECOM 2024, Vol. 237, p.139, Springer Nature
    🔎 Cited by: 2 articles

 

Muhammad Sajjad | Computer Science | Best Researcher Award

Posted on by Computer Scientists Awards

 Dr.  Muhammad Sajjad | Computer Science | Best Researcher Award

Faculty (Visiting), Quaid-I-Azam University Islamabad, Pakistan

Muhammad Sajjad is a Pakistani mathematician specializing in cybersecurity and cryptography. With a Ph.D. from Quaid-i-Azam University, his research focuses on advanced coding and cryptographic schemes, published extensively in renowned journals. He’s received numerous awards, including the International Research Award on Cybersecurity and Cryptography. Sajjad’s expertise extends to teaching and international collaborations, contributing significantly to academia. 🎓 His innovative work bridges theoretical mathematics with practical applications, ensuring data security in the digital age. 🛡️

Profile 

ORCID

🎓 Education

Muhammad Sajjad holds a Doctor of Philosophy (Ph.D.) in Mathematics from Quaid-i-Azam University, Islamabad. He also completed his Master of Philosophy (M.Phil.) and Master of Science (M.Sc.) degrees from the same institution.

💼 Experience

He has significant experience in academia, having taught various mathematics courses at Quaid-i-Azam University, National University of Modern Languages, Bahria University, and FG Sir Syed College. He has also been involved in research conferences and international collaborations.

🔍 Research Interests

Sajjad’s research interests span across several areas including Mathematics, Electrical Engineering, Vector Algebra, Non-commutative Algebra, Number Theory, Coding Theory, Channel Coding, and Cryptography.

🏆 Awards

He has received numerous awards and scholarships throughout his academic journey, including the International Research Award on Cybersecurity and Cryptography and being a finalist for PakCrypto by the National Centre for Cyber Security (NCCS).

📚 Publications

Sajjad, M., Shah, T., Haq, T.U., Almutairi, B., & Xin, Q., “SPN based RGB Image Encryption over Gaussian Integers,” Heliyon, vol. 10, 2024. Link (Cited by: 0)

Sajjad, M., & Shah, T., “Decoding of cyclic codes over quaternion integers by modified Berlekamp–Massey algorithm,” Computational and Applied Mathematics, 43(2), 2024. Link (Cited by: 0)

Sajjad, M., Shah, T., Alsaud, H., & Alammari, M., “Designing pair of nonlinear components of a block cipher over quaternion integers,” AIMS Mathematics, vol. 8, 2023. Link (Cited by: 0)

Sajjad, M., Shah, T., Xin, Q., & Almutairi B., “Eisenstein field BCH codes constructions and decoding,” AIMS Mathematics, vol. 8. Link (Cited by: 0)

Sajjad, M., Shah, T., Alammari, M., & Alsaud, H., “Construction and Decoding of BCH-Codes Over the Gaussian Field,” IEEE Access, vol. 11, 2023. Link (Cited by: 0)