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.

Meriem Smati | Engineering and Technology | Research Excellence Award

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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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Featured Publications

Sridevi S | Engineering and Technology | Best Researcher Award

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Dr. Sridevi S | Engineering and Technology | Best Researcher Award

Presidency University | India

Dr. Sridevi S is an accomplished Assistant Professor in Computer Science and Engineering with over seventeen years of academic experience and a Ph.D. completed. She is currently associated with the School of CSE at Presidency University, Bangalore, where she actively contributes to teaching, curriculum design, accreditation activities, and student mentoring. Her academic background includes a Ph.D. in Computer Science and Engineering, an M.Tech in Computer Science and Engineering with distinction, and a Bachelor’s degree in Information Science and Engineering, also with distinction. Dr. Sridevi has extensive experience delivering core and advanced courses such as Data Structures, Computer Networks, Data Mining, Web Technologies, Full Stack Development, and multiple programming languages. Her research interests span 5G and beyond wireless networks, machine learning applications, data analytics, wireless sensor networks, deep learning, and intelligent network optimization. She has published several articles in reputed Scopus-indexed journals and conferences, and her reflects an h-index of 1 with 8 published documents and approximately 2 citations. In addition to her research contributions, she has authored technical books and book chapters with leading publishers. She has been recognized as Best Faculty and has received institutional appreciation for her leadership as Cultural Coordinator. Dr. Sridevi’s career reflects a strong commitment to academic excellence, impactful research, industry-aligned teaching, and holistic student development.

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Featured Publications

DDM: Data-Driven Marketing Using AI, ML, and Big Data
N. N. Ahamed, S. Sridevi, AI-Powered Business Intelligence for Modern Organizations, IGI Global, pp. 79–102, 2025

Real-Time Interference Management in Next-Generation Wireless Systems
S. A. Abidi, D. P. P. D. Beemkumar Nagappan, S. Sridevi, Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 2025 (Scopus-Q2)

Heart Arrhythmia Classification Using Machine Learning Algorithms
V. Hiremani, R. M. Devadas, A. Pasha, S. Sridevi, 2nd International Conference on Ambient Intelligence in Health Care, 2023 (Scopus)

Child Safety & Tracking Management System Using GPS, Geo-Fencing and Android Application
S. Sridevi, S. Thakur, PiCES – Perspectives in Communication, Embedded Systems and Signal Processing, 2018

Indian Classical Percussion Instrument Tabla Taal Classification Using Fast Converging CNN
A. R. Sridevi S., Swati Sharma, Clara Kanmani, Nipun Sharma, Syed Abrar Ahmed, IEEE 4th World Conference on Applied Intelligence and Computing (AIC 2025), 2025 (Scopus)

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

Ganiyat Salawu | Engineering and Technology | Research Excellence Award

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Dr. Ganiyat Salawu | Engineering and Technology | Research Excellence Award

University of KwaZulu-Natal,Durban | South Africa

Dr. Ganiyat Abiodun Salawu is a mechanical and mechatronics engineer and researcher with strong expertise in advanced manufacturing systems, robotics, renewable energy technologies, and intelligent engineering solutions. She holds a PhD in Mechanical Engineering (Mechatronics and Robotics) from the University of KwaZulu-Natal, South Africa, following earlier degrees in mechanical engineering and education from Nigerian institutions. Her academic and professional career spans lecturing, postgraduate supervision, research coordination, and postdoctoral research, with extensive experience in both university and polytechnic systems. Her research interests focus on disruptive manufacturing technologies, IoT-based systems, renewable energy optimization, smart automation, tribology, composite materials, and sustainable engineering design. Dr. Salawu has authored over 20 peer-reviewed journal and conference publications, with an approximate h-index of 3, and over 20 cumulative citations based on available scholarly records. She has received multiple competitive research grants, including TETFund institutional and doctoral awards, and was honored with an Award of Excellence as Best Researcher by the University of KwaZulu-Natal. Through impactful research, supervision, and innovation-driven teaching, she continues to contribute significantly to engineering education, sustainable technology development, and applied industrial research in Africa and beyond.

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Featured Publications

Dike Chijindu P.; Sam Obu C.V.; Imuran A.S.; Salawu G.A.; Shuaib A.A. (2025).
Production and Mechanical Evaluation of Bio-Composite Materials from Coconut, Palm Kernel and Periwinkle Shells as an Alternative to Grinding Wheel Production.

International Journal of Applied and Advanced Engineering Research, Vol. 8, No. 5, 2025

Jimoh A.A.; Iromini N.A.; Oladuntoye Q.O.; Ajiteru S.O.; Salawu G.A. (2024).
Design and Deployment of an Internet of Things Based Weather Station for Real-Time Monitoring of Environmental Conditions.

International Journal of Earth Design and Innovation Research, Vol. 3, No. 4, 2024

Dike Chijindu P.; Sam Obu C.V.; Imuran A.S.; Salawu G.A.; Shuaib A.A.; Afolabi A.A. (2025).
Investigating the Mechanical Performance of Offshore Wind Turbine Towers Using Finite Element Analysis for Sustainable Renewable Energy.

Journal of Engineering, Logical and Modelling Research, 2025

Investigation of Technical Feasibility and Efficiency of Wi-Fi Based Internet of Things Remote Monitoring and Control of Home Appliances.

International Journal of Science Research and Technology, Vol. 6, No. 9, pp. 121–135, 2024

Design and Development of Internet of Things Based Weather Station for Real-Time Monitoring of Environmental Conditions.

International Journal of Earth Design and Innovation Research, Vol. 3, No. 4, pp. 66–75, 2024

Ho-jun Song | Computer Science and Artificial Intelligence | Research Excellence Award

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Mr. Ho-jun Song | Computer Science and Artificial Intelligence | Research Excellence Award

Postech | South Korea

Ho-jun Song is a dedicated researcher and Ph.D. candidate in Computer Science and Engineering, specializing in federated learning, edge intelligence, and AIoT systems. With an academic foundation grounded in advanced distributed learning, he has contributed to developing personalized, scalable, and diffusion-based FL frameworks tailored for heterogeneous and resource-constrained environments. He has gained extensive experience through work on edge AI architectures, large-scale experimental pipelines, and applied AI systems for surveillance, security, and military decision support. Professionally, he leads AI initiatives as the Head of AI Development at the Army Artificial Intelligence Center, overseeing deepfake detection, ontology-based LLM systems, and intelligent multi-sensor surveillance solutions. His research interests span federated learning, personalized models, diffusion-based FL, distributed deep learning, and AIoT innovation. His academic journey includes rigorous research under expert mentorship and collaborations with interdisciplinary teams. Although early in his career, he has already contributed impactful ideas such as multidimensional trajectory optimization for FL personalization. He aspires to advance secure, efficient, and adaptive AI systems while contributing to global AI research communities through innovative, mission-driven research.

Profile : Orcid

Featured Publications

Song, H.-J., & Suh, Y.-J. (2025). HyFLM: A hypernetwork-based federated learning with multidimensional trajectory optimization on diffusion paths. Electronics, 14, Article 4704.