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

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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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Dongju Yang | Computer Science and Artificial Intelligence | Research Excellence Award

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Dr. Dongju Yang | Computer Science and Artificial Intelligence | Research Excellence Award

North China University of Technology | China

Dr. Dongju Yang is an Associate Researcher and Assistant Lead Professor for Artificial Intelligence at North China University of Technology, with over a decade of academic and research experience in intelligent computing systems. She earned her Ph.D. in Computer Software and Theory from Northwestern Polytechnical University and previously conducted advanced research at the Institute of Computing Technology, Chinese Academy of Sciences. Her research focuses on Large Language Models, Retrieval-Augmented Generation (RAG), AI Agents, Knowledge Graphs, Natural Language Processing, Service Computing, and Data Intelligence, with strong application impact in smart elderly care and intelligent education. Dr. Yang has led more than ten competitive research projects as principal investigator, including a sub-project of China’s National Key R&D Program and an NSFC General Program, while contributing to multiple major national initiatives. She has contributed to one national standard and three group standards and received the Beijing Science and Technology Progress Award. Overall, her work bridges fundamental AI research with scalable, real-world technological impact and talent cultivation.


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Featured Publications

Intelligent Orientation Robot Based on Large Language Models and Retrieval-Augmented Generation
Dongju Yang, 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE), 2024. (WOS)

Multi-source Autoregressive Entity Linking Based on Generative Method
Dongju Yang, Weishui Lan, Communications in Computer and Information Science, 2024. (Book Chapter)

IoT Service Distributed Management Architecture and Service Discovery Method for Edge-Cloud Federation
Dongju Yang, International Journal of Grid and Utility Computing, 2022. (WOS)

Construction and Analysis of Scientific and Technological Personnel Relational Graph for Group Recognition
Dongju Yang, International Journal of Software Engineering and Knowledge Engineering, 2021. (WOS)

Research on User Demand-Driven Service Matching Methodology
Huiying Zhang, Dongju Yang, IEEE 6th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), 2021.

Jingyuan Zhao | Energy and Sustainability | Research Excellence Award

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Dr. Jingyuan Zhao | Energy and Sustainability | Research Excellence Award

University of California Davis | United States

Jingyuan (Andy) Zhao, Ph.D., is an Assistant Professional Researcher and independent principal investigator at the University of California, Davis, internationally recognized for pioneering work in AI-enabled battery and energy systems. His research integrates multiphysics and multiscale modeling with advanced artificial intelligence to address battery safety, diagnostics, prognostics, and system-level optimization for electrified transportation.  He has led or co-led major U.S. and international research projects supported by USDOT, Caltrans, CEC, CARB, and national science foundations in China, while also translating research into industrial impact through prior leadership roles in electric vehicle battery intelligence. His academic training spans mechanical and vehicle engineering, complemented by extensive postdoctoral research in the U.S. and China. Dr. Zhao has received numerous honors, including Elsevier–Stanford World’s Top 2% Scientist and ScholarGPS Top 0.5% Scholar distinctions. Through interdisciplinary scholarship, global collaboration, and mentorship, his work advances safe, intelligent, and scalable battery energy systems, bridging laboratory innovation with real-world deployment and shaping the future of sustainable mobility.

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Featured Publications


Review on Supercapacitors: Technologies and Performance Evaluation
J. Zhao, A.F. Burke, Journal of Energy Chemistry, 59, 276–291, 2021. (Citations: 602)


Autonomous Driving System: A Comprehensive Survey
J. Zhao, W. Zhao, B. Deng, Z. Wang, F. Zhang, et al., Expert Systems with Applications, 242, 122836, 2024. (Citations: 330)


Electrochemical Capacitors: Materials, Technologies and Performance
J. Zhao, A.F. Burke, Energy Storage Materials, 36, 31–55, 2021. (Citations: 202)


Electrochemical Capacitors: Performance Metrics and Evaluation by Testing and Analysis
J. Zhao, A.F. Burke, Advanced Energy Materials, 11(1), 2002192, 2021. (Citations: 182)


Machine Learning for Predicting Battery Capacity for Electric Vehicles
J. Zhao, H. Ling, J. Liu, J. Wang, A.F. Burke, Y. Lian, eTransportation, 15, 100214, 2023. (Citations: 171)

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

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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

Chahira Cherif | Computer Science and Artificial Intelligence | Research Excellence Award

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Dr. Chahira Cherif | Computer Science and Artificial Intelligence | Research Excellence Award

Université Oran 1 | Algeria

Dr. Chahira Cherif is an Associate Professor of Computer Science with a strong academic and research profile in higher education and software systems research. She holds a State Engineering degree in Computer Science, a Magister (Master’s) degree, and a Ph.D. in Computer Science, reflecting a solid and progressive academic foundation in computing and information technologies. Her professional experience includes service as a State Computer Science Engineer before transitioning into academia, where she has been actively engaged in teaching at both Bachelor’s and Master’s levels under the LMD system, along with supervising Master’s theses. Her research interests focus on intelligent software systems, software evolution, system security, and advanced computing methodologies, with active involvement in nationally recognized research initiatives, including the PREFU project on intelligent evolution and security of software systems. She has participated in international conferences, workshops, and scientific gatherings across Algeria and France, contributing to scholarly exchange and collaboration. Her scientific output is reflected through peer-reviewed publications indexed in international databases, with an established h-index-1 supported by multiple research documents-5 and citation-4 records. Through her combined roles as educator, researcher, and project contributor, she continues to make meaningful contributions to computer science research and academic development, strengthening innovation, knowledge dissemination, and the advancement of intelligent and secure software systems.

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Featured Publications


Predictive approach to the degree of business process change

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


Change impact study by Bayesian networks

C. Cherif, M.K. Abdi
Modeling Approaches and Algorithms for Advanced Computer Applications, pp. 429–438, 2013 · Citations: 5


Cancer classification through the selection of genes extracted from microarray data

M. Maiza, S. Chouraqui, C. Cherif, A. Taleb-Ahmed
Przegląd Elektrotechniczny, 101(4), 2025 · Citations: 4


Étude de l’impact de changement dans les systèmes à objet par les réseaux bayésiens

C. Chahira, A. Mustapha Kamel
Communication Science et Technologie, 13(1), pp. 90–108, 2015 · Citations: 4


Towards a probabilistic approach for better change management in BPM systems

C. Cherif
IEEE 23rd International Enterprise Distributed Object Computing Conference, 2019 · Citations: 3

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

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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

Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

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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

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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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Amir Hossein akbari | Engineering and Technology | Research Excellence Award

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Dr. Amir Hossein akbari | Engineering and Technology | Research Excellence Award

Iran University of Science and Technology | Iran

Amir Hosein Akbari is an accomplished researcher in industrial engineering with a strong record of scholarly impact his academic background is grounded in advanced industrial engineering education, complemented by progressive research experience spanning optimization, decision sciences, and intelligent systems. His professional experience includes active involvement in high-quality research collaborations and contributions to applied and theoretical studies addressing complex industrial and societal problems. His core research interests focus on supply chain management, optimization, meta-heuristic and evolutionary algorithms, scheduling, decision support systems, and artificial intelligence–driven industrial applications, with several influential works in expert systems, soft computing, and manufacturing systems. His publications have appeared in high-impact venues such as Expert Systems with Applications, Soft Computing, and Neural Computing and Applications, reflecting both methodological rigor and practical relevance. Recognition of his work is demonstrated through strong citation performance and collaborations with well-established scholars in operations research and industrial engineering. Overall, his research portfolio highlights a consistent commitment to advancing intelligent optimization methods and decision-making frameworks, contributing valuable insights to academia and industry while strengthening the scientific foundations of modern industrial engineering.

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