Nafiz Fahad | Computer Science | Best Researcher Award

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Mr. Nafiz Fahad | Computer Science | Best Researcher Award

Multimedia University | Malaysia

Mr. Nafiz Fahad is an emerging AI researcher at Multimedia University, Cyberjaya, Malaysia, recognized for his growing contributions to artificial intelligence in healthcare, computer vision, and natural language processing. His research focuses extensively on explainable AI, clinical decision support systems, and data-driven healthcare intelligence. According to Scopus, he has 19 indexed publications, 122 citations, and an h-index of 6, reflecting the influence and visibility of his scholarly work within the global research community. His scientific output spans chronic disease prediction, dementia analytics, lung disease classification, hypertension ontology development, wound-image segmentation, obesity prediction, and precision public health. These studies incorporate techniques such as deep learning, transfer learning, ensemble learning, hybrid architectures, and explainable machine learning to advance diagnostic accuracy and interpretability in medical AI systems. Beyond health-focused research, Fahad has also contributed high-impact work in fake news detection, generative AI, machine learning security, student performance prediction, agricultural disease detection, vision transformers for physics data, and federated learning enhanced with homomorphic encryption. His ongoing research extends to mental health analytics, EEG decoding models, diabetic retinopathy detection, and agentic AI solutions for healthcare innovation. Fahad’s growing academic recognition includes research awards, best paper achievements, and contributions to high-impact journals and conferences. His multidisciplinary scholarship positions him as a promising young researcher advancing applied AI at the intersection of healthcare, societal well-being, and intelligent systems.

Profiles: Scopus | Google Scholar | LinkedIn

Featured Publications

1. Ahmed, Z., Shanto, S. S., Rime, M. H. K., Morol, M. K., Fahad, N., Hossen, M. J., … (2024). The generative AI landscape in education: Mapping the terrain of opportunities, challenges and student perception. IEEE Access.

2. Mahamud, E., Fahad, N., Assaduzzaman, M., Zain, S. M., Goh, K. O. M., & Morol, M. K. (2024). An explainable artificial intelligence model for multiple lung diseases classification from chest X-ray images using fine-tuned transfer learning. Decision Analytics Journal, 12, 100499.

3. Ahmed, R., Fahad, N., Miah, M. S. U., Hossen, M. J., Morol, M. K., Mahmud, M., … (2024). A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction. Healthcare Analytics, 6, 100362.

4. Fahad, N., Goh, K. M., Hossen, M. I., Shopnil, K. M. S., Mitu, I. J., Alif, M. A. H., & Tee, C. (2023). Stand up against bad intended news: An approach to detect fake news using machine learning. Emerging Science Journal, 7(4), 1247–1259.

5. Hossain, M. N., Fahad, N., Ahmed, R., Sen, A., Al Huda, M. S., & Hossen, M. I. (2024). Preventing student’s mental health problems with the help of data mining. International Journal of Computing, 23(1), 101–108.

Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

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Dr. Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

University of Sydney | Australia

Dr. Mehnaz Tabassum is an accomplished researcher in Computational Neurosurgery and Health Innovation, with core expertise in medical image analysis, artificial intelligence, and brain tumor diagnostics. Her research integrates deep learning, radiomics, and neuroimaging to enhance the precision of tumor segmentation, classification, and recurrence prediction in neuro-oncology. Her scholarly contributions include 14 Scopus-indexed publications, with a total of 87 citations and an h-index of 4 (Scopus metrics). She has published in prestigious journals such as Cancers, European Radiology, and Neuro-Oncology Advances, and has presented her findings at leading international conferences including IEEE EMBC and IEEE ISBI. Dr. Mehnaz Tabassum’s recent research explores cross-modality medical image synthesis, MRI-to-PET generation using diffusion and GAN-based models, and meta transfer learning for brain tumor segmentation. Her innovative work advances computational solutions for precision medicine and AI-assisted neuroimaging. She has received multiple distinctions, including the Pro-Vice Chancellor’s Research Excellence Scholarship and the Henry Sutton Postgraduate Research Scholarship, alongside a Best Paper Award for excellence in scientific contribution. Her interdisciplinary research continues to impact the fields of AI-driven diagnostics, eye-tracking in medical imaging, and computational modeling for neurosurgical innovation, reflecting her commitment to advancing data-driven healthcare and translational neuroscience.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | Staff Page

Featured Publications

  • Tabassum, M., Suman, A. A., Suero Molina, E., Pan, E., Di Ieva, A., & Liu, S. (2023). Radiomics and machine learning in brain tumors and their habitat: A systematic review. Cancers, 15(8), Article 2034. https://doi.org/10.3390/cancers15082034

  • Ghose, P., Alavi, M., Tabassum, M., Ashraf Uddin, M., Biswas, M., Mahbub, K., … & Hassan, M. (2022). Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach. Frontiers in Genetics, 13, 980338. https://doi.org/10.3389/fgene.2022.980338

  • Moradizeyveh, S., Tabassum, M., Liu, S., Newport, R. A., Beheshti, A., & Di Ieva, A. (2024). When eye-tracking meets machine learning: A systematic review on applications in medical image analysis. arXiv preprint arXiv:2403.07834. https://arxiv.org/abs/2403.07834

  • Tabassum, M., Suman, A. A., Russo, C., Di Ieva, A., & Liu, S. (2023). A deep learning framework for skull stripping in brain MRI. Neurocomputing (Under review).

  • Afrin, F., Al-Amin, M., & Tabassum, M. (2015). Comparative performance of using PCA with K-means and fuzzy C means clustering for customer segmentation. International Journal of Scientific and Technology Research, 4(8), 70–74.

Sam Clarke | Computer Science | Best Researcher Award

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Mr. Sam Clarke | Computer Science | Best Researcher Award

Canterbury Christ Church University | United Kingdom

Sam Clarke is a dynamic and forward-thinking educator with over eight years of experience as a class teacher across Key Stages 1 and 2, and a key contributor to senior leadership teams. With a career rooted in both classroom practice and strategic educational leadership, Sam has transitioned seamlessly into higher education as a Lecturer of Primary Education at Canterbury Christ Church University. His expertise spans teaching, mentoring, research, and academic innovation, particularly in the realm of artificial intelligence (AI) in education. A passionate advocate for equity and ethical innovation, Sam combines classroom experience with pioneering research, curriculum design, and community outreach. His professional philosophy echoes Nelson Mandela’s powerful belief that “Education is the most powerful weapon to change the world.”

Professional profile👤

ORCID

Strengths for the Awards✨

  1. Innovative Research in AI and Education
    Sam Clarke’s work sits at the intersection of two rapidly evolving fields: education and artificial intelligence. His research addresses critical questions about GenAI’s impact on pedagogy, curriculum design, and interdisciplinary learning. His publication “Education in the Age of GenAI” and his co-edited journal BQIL demonstrate a commitment to pioneering research.

  2. Leadership in Academic Initiatives
    Sam is not just a participant but a leader in several academic and professional settings. As Founding Co-Editor of BQIL, Peer Reviewer for research funding, and Lecturer at CCCU, he has shown initiative and scholarly leadership.

  3. Policy-Relevant Contributions
    His guest lectures at UCL, Cambridge, and the Association of Citizenship Teaching suggest his work resonates beyond academia. He connects research to practice, influencing national discourse on AI in education.

  4. Community Engagement and Equity
    Through outreach in underprivileged schools and staff CPD on AI literacy, Sam applies his research to reduce educational inequities, making a tangible social impact.

  5. Collaborative and Interdisciplinary Work
    Clarke’s collaboration with prestigious institutions like the University of Oxford and his emphasis on interdisciplinary knowledge building demonstrate a wide-ranging and cooperative research ethos.

  6. Strong Publication Record with Open Access & Accessibility
    His commitment to knowledge dissemination is evident in his open-access publications and engagement in practitioner journals, ensuring that research reaches a diverse audience.

🎓 Education

Sam’s educational journey reflects a consistent trajectory of academic excellence and professional growth. He holds a Bachelor of Arts in Education Studies and Geography (First Class, 2014), a Postgraduate Certificate in Education with QTS (Distinction, 2015), and a Master of Arts in Education (Merit, 2024)—all from Canterbury Christ Church University. Most recently, he achieved a University Certificate of Advanced Practice (Distinction, 2025), further cementing his commitment to lifelong learning and pedagogical excellence.

👨‍🏫 Experience

Sam began his teaching career in 2015, serving in various roles including KS1 and KS2 Teacher, Mathematics Lead, and Computing Lead. His leadership capabilities emerged early, culminating in a place on the Senior Leadership Team at Sussex Road Primary School, where he managed appraisals, led curriculum initiatives, and coached newly qualified teachers. From 2017 to 2019, Sam also contributed as a School Improvement Facilitator for the Education Development Trust. Transitioning into higher education in 2024, he now lectures at Canterbury Christ Church University, shaping future educators with research-informed teaching and innovation-driven curriculum design.

🔬 Research Interests On Computer Science

Sam’s primary research interests lie in the ethical and educational implications of Generative AI within primary and higher education settings. He is especially passionate about exploring how AI can foster interdisciplinary learning, democratize access to education, and promote epistemic insight. His involvement with the Professoriate Group on AI and as a board member of the AI Ethics Committee at UCL underscores his commitment to ethical innovation. Sam also co-founded the academic journal Big Questions and Interdisciplinary Learning, promoting complex thinking and boundary-crossing knowledge creation.

🏆 Awards

Sam has not only received academic distinctions across all his university qualifications, but has also been repeatedly entrusted with leadership and mentoring roles that reflect his excellence. His invitation to prestigious conferences and involvement in ethics committees, editorial boards, and university strategic roles stands as a testament to the recognition of his thought leadership within the educational community.

📄 Publications

Sam Clarke has authored and co-authored several impactful publications exploring the intersections of education and AI:

  • Clarke, S. and Billingsley, B. (2024). Education in the Age of GenAI. Cambridge Generative AI in Education Conference Booklet of Abstracts.
    Published in 2024 | Cited by 3 articles

  • Clarke, S. (2024). A General Election and My Classroom in the Age of AI. Teaching Citizenship, Issue 59, pp. 8–9.
    Published in 2024 | Cited by 1 article

  • Clarke, S., Billingsley, B., & Heath, L. (Eds.) (2024). Big Questions and Interdisciplinary Learning. Zenodo.
    Published in 2024 | Cited by 2 articles

  • Clarke, S., Billingsley, B. and O’Leary, S. (2024). Using Generative Artificial Intelligence to Catalyse Further Interdisciplinarity Across Higher Education. Graduate College Working Papers, CCCU. Read paper
    Published in 2024 | Cited by 4 articles

✅ Conclusion

Sam Clarke embodies the ideal fusion of practitioner expertise and academic innovation. His contributions to AI in education—through teaching, research, publication, and community outreach—are both timely and transformative. With a consistent record of academic achievement, leadership, and ethical vision, Sam is poised to continue shaping the future of education at the intersection of pedagogy and technology. His work reflects a profound dedication to empowering educators and learners alike in a rapidly evolving digital world. 🌟