Bilal Khan | Engineering and Technology | Research Excellence Award

Dr. Bilal Khan | Engineering and Technology | Research Excellence Award

Department of Computer Science, University of Engineering and Technology, Mardan | Pakistan

Dr. Bilal Khan is a research‑driven academic with a Ph.D. in Computer Software Engineering and more than 15 years of university‑level teaching and research experience across leading higher‑education institutions in Pakistan, including University of Engineering & Technology, Mardan; City University of Science and Information Technology, Peshawar; Northern University, Nowshera; University of Swabi; and National Institute of Technology, Akora Khattak. His scholarly work focuses on Machine Learning, Data Science, Natural Language Processing, Healthcare & Bioinformatics Analytics, and Software Engineering, where he has authored a substantial portfolio of international journal publications indexed in venues such as IEEE Access and Journal of Healthcare Engineering. Dr. Khan has played key roles in curriculum development, postgraduate supervision, and academic coordination, and serves as a reviewer for high‑impact journals including IEEE Access, ACM Transactions on Healthcare, and Artificial Intelligence. His interdisciplinary work bridges theory and practice, and he remains actively engaged in collaborative research, external grant pursuits, and innovative solutions addressing real‑world challenges.

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Featured Publications

An empirical evaluation of machine learning techniques for chronic kidney disease prophecy
Khan, B., Naseem, R., Muhammad, F., Abbas, G., Kim, S., 2020.

Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques
Khan, B., Naseem, R., Shah, M.A., Wakil, K., Khan, A., Uddin, M.I., Mahmoud, M., Journal of Healthcare Engineering, 2021.

An Overview of ETL Techniques, Tools, Processes and Evaluations in Data Warehousing
Khan, B., Jan, S., Khan, W., Chughtai, M.I., Journal on Big Data, 6, 2024.

Performance assessment of classification algorithms on early detection of liver syndrome
Naseem, R., Khan, B., Shah, M.A., et al., Journal of Healthcare Engineering, 2020.

Exploring the landscape of automatic text summarization: a comprehensive survey
Khan, B., Shah, Z.A., Usman, M., Khan, I., Niazi, B., IEEE Access, 11,  2023.

Mona Ali | Computer Science and Artificial Intelligence | Research Excellence Award

Prof. Mona Ali | Computer Science and Artificial Intelligence | Research Excellence Award

King Faisal University | Saudi Arabia

Dr. Mona Abdelbaset Sadek Ali is an Associate Professor of Computer Science specializing in artificial intelligence, machine learning, and image processing. She earned her PhD in Computer Science (Wireless Computer Communications) from Cardiff University, UK, after completing an MSc in Information Technology (Image Processing) and a BSc in Information Technology with honors from Cairo University. With extensive academic experience spanning the UK, Saudi Arabia, and Egypt, her research integrates deep learning, optimization techniques, computer vision, IoT, mobile security, and intelligent healthcare systems. Dr. Ali has authored over 30 peer-reviewed research articles published in high-impact Web of Science-indexed journals and conferences, achieving an h-index of approximately 17, with more than 871 citations and 29 research documents. Her work frequently appears in Q1 and Q2 journals such as Mathematics, Electronics, Sustainability, PLOS ONE, and Applied Sciences. She has led and co-led numerous funded research projects supported by national and institutional bodies and has supervised multiple postgraduate MSc and PhD researchers. Her academic excellence has been recognized through competitive research funding and research poster awards. Overall, Dr. Ali’s career reflects sustained contributions to applied artificial intelligence and data-driven solutions with strong interdisciplinary and societal impact.

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Featured Publications


Tomato leaves diseases detection approach based on support vector machines

11th International Computer Engineering Conference (ICENCO), 246–250, 2015 · Citations: 222


Identifying two of tomatoes leaf viruses using support vector machine

Information Systems Design and Intelligent Applications, 2015 · Citations: 145


Detection of breast abnormalities of thermograms based on a new segmentation method

Federated Conference on Computer Science and Information Systems, 2015 · Citations: 78


Thermogram breast cancer prediction approach based on neutrosophic sets and fuzzy c-means algorithm

IEEE Engineering in Medicine and Biology Conference, 2015 · Citations: 76


A hybrid segmentation approach based on neutrosophic sets and modified watershed: A case of abdominal CT liver parenchyma

11th International Computer Engineering Conference (ICENCO), 2015 · Citations: 70

Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Mr. Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Ecole Polytechnique de Tunisie | Tunisia

Oussama El Othmani is an emerging researcher and software engineer whose work bridges artificial intelligence, explainable machine learning, and applied computer engineering. He is currently pursuing a PhD in ETIC, following a strong academic foundation in computer engineering and preparatory mathematics–physics, with rigorous training in artificial intelligence, advanced learning algorithms, computer architecture, databases, and software methodology. Professionally, he has contributed to complex, mission-critical software systems, working across the full software development lifecycle while applying agile methodologies, object-oriented design, and hardware-aware optimization. His research interests focus on explainable and interpretable AI, machine learning, rough set theory, soft computing, computer vision, natural language processing, and AI applications in healthcare and high-stakes decision systems. He has led and contributed to multiple applied AI projects, including medical chatbots, diagnostic decision-support systems, blood anomaly detection, and antibiotic resistance classification. His scholarly output includes peer-reviewed publications in applied AI, He has also gained recognition through research-driven projects aligned with national and institutional initiatives. Overall, his profile reflects a strong balance of academic research, applied innovation, and real-world impact, positioning him as a promising contributor to the future of trustworthy and explainable artificial intelligence.

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David Owolabi | Civil Engineering | Best Researcher Award

Mr. David Owolabi | Civil Engineering | Best Researcher Award

Morgan State University | United States

Mr. David Olusogo Owolabi is a researcher and educator specializing in sustainable infrastructure and resilient engineering. He holds a PhD (in progress) and an MSc in Sustainable Infrastructure and Resilient Engineering from Morgan State University, and a BSc in Architecture from Caleb University. In his role as a Graduate Research & Teaching Assistant at Morgan State, he supports undergraduate lab instruction in CAD and structural analysis (SAP2000) while conducting experimental research in self-healing bacterial concrete, fiber integration, and MICP-based crack remediation. Earlier, as an Architectural Designer at Kreativity Projects (Lagos) and an intern at Ab.dt Partnership (Ibadan), he developed design concepts, 3D visualizations, working drawings, and integrated sustainable design principles. His research interests span microbial self-healing concrete, bio-based infrastructure resilience, green building practices, and material durability. His published works include comparative analyses of autogenous vs microbial calcite precipitation in concrete and studies on crack healing performance via microbial carriers. He has also contributed to interdisciplinary studies on air quality in engineering labs and noise mitigation in buildings. He is a certified professional in Autodesk Revit and AutoCAD, has earned certifications in machine learning and socially just coding, and is committed to applying data-driven, sustainable innovation in civil infrastructure.

Profile : Google Scholar 

Featured Publications

Ahmad, I., Shokouhian, M., Owolabi, D., Jenkins, M., & McLemore, G. L. (2025). Assessment of biogenic healing capability, mechanical properties, and freeze–thaw durability of bacterial-based concrete using Bacillus subtilis, Bacillus sphaericus, and Bacillus megaterium. Buildings, 15(6), 943.

Ahmad, I., Shokouhian, M., Jenkins, M., McLemore, G. L., & Owolabi, D. O. (2025). Crack healing performance of microbial self-healing concrete using different carriers. In Structures Congress 2025 (pp. 362–372). American Society of Civil Engineers.

Owolabi, D. O., Shokouhian, M., Ahmad, I., Jenkins, M., & McLemore, G. L. (2025). Comparative analysis of autogenous and microbial-based calcite precipitation in concrete: State-of-the-art review. Buildings, 15(18), 3289.

Dunmoye, A. C., Owolabi, O. A., Banjo, A. V., Abiri, T. I., Dunmoye, I. D., & Owolabi, D. O. (2025). Noise mitigation strategies for vertical sound transmission in buildings with wooden floor. INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 271(1), 1009–1018.

Balogun, G. Y., Owolabi, D. O., Ige, M. O., Abiri, T., Abiodun, P. O., & Owolabi, O. A. (2025). Assessing air quality at HBCU engineering laboratories to enhance student safety and learning. 2025 ASEE Annual Conference & Exposition. American Society for Engineering Education.