Norhazwani Md Yunos | Data Science and Analytics | Research Excellence Award

Dr. Norhazwani Md Yunos | Data Science and Analytics | Research Excellence Award

Universiti Teknikal Malaysia Melaka | Malaysia

Dr. Norhazwani Md Yunos is an accomplished computer scientist and academic whose work bridges theoretical algorithms and applied data analytics. She has authored 11 Scopus-indexed documents, receiving 68 citations with an h-index of 4, reflecting steady scholarly impact across multiple domains. Her educational background is grounded in computer science and algorithmic research, with strong foundations in graph theory, optimization, and computational complexity. Over her academic career, she has gained extensive experience as a lecturer and researcher, contributing to both fundamental theory and real-world applications. Her research interests span machine learning, sentiment analysis, network and community detection, optimization algorithms, big data analytics, and combinatorial optimization, including notable contributions to polynomial-space exact algorithms for the Traveling Salesman Problem (TSP) and modern studies on dynamic community detection and data-driven classification models. Dr. Md Yunos has published in reputable journals such as Alexandria Engineering Journal, Pertanika Journal of Science and Technology, and Journal of Electronic Materials, demonstrating interdisciplinary reach from algorithm design to intelligent systems. Her scholarly record includes peer-reviewed journal articles, conference papers, and book chapters, alongside recognition through high citation performance in selected works. Overall, her research portfolio highlights a sustained commitment to advancing computational methods, intelligent data analysis, and algorithmic efficiency for contemporary scientific and industrial challenges.

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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.

Meriem Smati | Engineering and Technology | Research Excellence Award

Ms. Meriem Smati | Engineering and Technology | Research Excellence Award

INSA Lyon – Polytechnique Montreal | France

Meriem Smati is a doctoral researcher in a dual-degree PhD program in Computer Science and Industrial Engineering at INSA Lyon and Polytechnique Montréal, focusing on advanced digital engineering and intelligent systems. She holds an Engineer and Master’s degree in Systems Engineering from the Higher School of Computer Science (ESI SBA) and a Bachelor’s degree in Information Systems and Software Engineering, graduating as valedictorian. Her academic and professional experience includes PhD-level research, adjunct lecturing in computer science, and multiple international research internships. Her research interests center on Digital Twins, System-of-Systems engineering, resilience modeling, cognitive and data-driven twins, IoT systems, anomaly detection, and smart city applications, integrating machine learning and simulation-based architectures. She has authored and co-authored peer-reviewed journal and conference publications, a scientific book, and several applied research reports. Her scholarly output is reflected in an approximate. Her work has been recognized through prestigious distinctions, including Best Paper and Best Poster awards at international conferences. Overall, her profile reflects a dynamic early-career researcher contributing impactful methodologies and architectures for resilient, intelligent, and sustainable digital systems.

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Mohammed Maiza | Computer Science and Artificial Intelligence | Research Excellence Award

Dr. Mohammed Maiza | Computer Science and Artificial Intelligence | Research Excellence Award

Université Oran 1 | Algeria

Dr. Mohammed Maiza is an Associate Professor of Computer Science specializing in Pattern Recognition and Artificial Intelligence, with a strong academic and research profile in intelligent systems and data-driven computing. He holds an engineering degree in Computer Science with a specialization in Artificial Intelligence, followed by a Magister and Ph.D. in Computer Science focused on Pattern Recognition and AI. His academic career includes long-standing experience as a Lecturer-Researcher at leading Algerian universities, where he has contributed extensively to teaching, research supervision, and academic leadership. His research interests span pattern recognition, machine learning, artificial intelligence, data analysis, and intelligent decision-support systems. Dr. Maiza has actively participated in international conferences, workshops, and research visits in Algeria and France, strengthening collaborative research networks. He has authored multiple peer-reviewed scientific publications indexed in international databases, with measurable scholarly impact reflected through his h-index, citation count, and documented research outputs in major indexing platforms. In addition to research, he has held several academic leadership and coordination roles, contributing to curriculum development and institutional governance. His academic contributions demonstrate a sustained commitment to advancing AI research, mentoring graduate students, and fostering innovation in computer science, positioning him as a respected researcher and educator in the field.

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Featured Publications

C. Cherif, M.K. Abdi, A. Ahmad, M. Maiza
International Journal of Computing and Digital Systems, 14(1), 10505–10513, 2023 · Citations: 5

M. Maiza, S. Chouraqui, C. Cherif, A. Taleb-Ahmed
Przegląd Elektrotechniczny, 2025(4), 2025 · Citations: 4

A. Ahmad, M. Bouneffa, H. Basson, C. Cherif, M.K. Abdi, M. Maiza
Enterprise Interoperability X: Enterprise Interoperability Through Connected Enterprises, 2024 · Citations: 1

C. Cherif, M. Maiza, S. Chouraqui, A. Taleb
13th European Workshop on Visual Information Processing (EUVIP), pp. 1–6, 2025

C. Cherif, M. Maiza, S. Chouraqui, A. Taleb-Ahmed
Informatica, 49(3), 2025

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

Zohaib Khan | Engineering and Technology | Excellence in Research Award

Dr. Zohaib Khan | Engineering and Technology | Excellence in Research Award

Jiangsu University | China

Zohaib Khan is a PhD candidate in Control Science and Engineering at Jiangsu University, specializing in machine learning–driven perception and control for intelligent robotic systems. With over six years of research and applied experience, his work bridges deep learning, computer vision, and real-time robotic control, with a strong focus on agricultural robotics and precision farming. He has authored more than 10 high-impact SCI-indexed journal articles, achieving an h-index of 6, with 11 research documents and 121 citations. His research interests include object detection and segmentation (YOLO series, transformer-based models, RCNN), vision-guided navigation, precision spraying, and robust control of autonomous robots in unstructured environments. Zohaib has contributed as both first and co-author to leading journals such as Computers and Electronics in Agriculture, Agronomy, Sensors, and IEEE Transactions on Industrial Electronics. Alongside research, he has extensive experience supervising student projects and developing real-time AI pipelines using Python, PyTorch, OpenCV, ROS, and C/C++. His academic excellence is recognized through multiple national and international awards, including innovation, debate, and research excellence honors. Overall, Zohaib Khan represents a strong blend of theoretical rigor and practical AI deployment, aiming to advance large-scale industrial and agricultural perception systems.

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Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

Mr. Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

King Fahd University of Petroleum and Minerals | Saudi Arabia

Ibrahim Khalil Kabir is a control and robotics researcher working at the intersection of control theory and artificial intelligence, with a strong focus on learning-based robotics, socially aware navigation, and human–robot interaction. He holds an MSc in Systems and Control Engineering and a BEng in Mechatronics Engineering, with a solid academic record and advanced training in autonomous systems. His research experience spans graduate teaching and research assistantships, where he contributed to robot path planning, navigation, and hands-on laboratory instruction using real robotic platforms. His scholarly output includes peer-reviewed journal and conference publications covering UAV control, mobile robot navigation, deep reinforcement learning, and socially aware robotic systems. According to Google Scholar, his research profile reflects an emerging h-index supported by multiple indexed documents and a steadily growing citation count, indicating increasing impact in robotics and intelligent control research. His work has appeared in reputable venues such as IEEE Access, Machine Learning and Knowledge Extraction, and IEEE conferences. He has received several academic honors, including national merit scholarships and highest GPA awards. Overall, his research trajectory demonstrates a strong foundation and growing influence in intelligent robotics, positioning him well for advanced doctoral research in learning-enabled autonomous systems.

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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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Liu Ying | Mechanical Engineering | Research Excellence Award

Dr. Liu Ying | Mechanical Engineering | Research Excellence Award

East China Jiaotong University | China

Ying Liu is a dedicated researcher and Lecturer specializing in vehicle engineering with a strong academic trajectory and growing research impact, reflected in an h-index of 2, 4 published documents, and 14 citations across indexed platforms. She earned a combined Master’s and PhD degree in Mechanical Engineering from Shanghai University, followed by a Bachelor’s degree in Mechanical Design, Manufacturing and Automation from Changchun Institute of Technology. Her professional career includes serving as a Lecturer at East China Jiaotong University, where she contributes to teaching, mentoring, and interdisciplinary research. Her work focuses on target optimization, image detection, reinforcement learning, computer vision, intelligent control, and smart vehicle technologies. She has completed five research projects, contributed to two national-level and multiple provincial and horizontal projects, and actively engages in consultancy with ten industry-linked initiatives. She has authored seven SCI-indexed papers, produced twenty-five patents, and participated in major scientific collaborations including a project funded with 5 million yuan. As a recipient of Jiangxi’s Early-Career Young Talents Program, she continues to advance innovation in intelligent vehicle systems. She remains committed to impactful research, advancing engineering applications, and contributing to societal and technological development.

Profile : Scopus

Featured Publications

Liu, Y., & [Co-author(s) if any]. (2025). Continuous path tracking of robots based on positioning error compensation with iterative learning control. IEEE Transactions on Instrumentation and Measurement.