Rania Hamdani | Computer Science and Artificial Intelligence | Best Researcher Award

Ms. Rania Hamdani | Computer Science and Artificial Intelligence | Best Researcher Award

AE3S at University of luxembourg, Luxembourg 

Rania Hamdani is a dynamic early-career research scientist specializing in software engineering, data management, and cloud architecture for Industry 5.0 applications. Currently based at the University of Luxembourg, she is engaged in advanced research on integrating heterogeneous data sources and optimizing decision-making in cloud-based systems. With a strong foundation in software development and operational research, Rania has already co-authored three research papers in Cloud-Edge AI and ontology-driven knowledge management. Her diverse technical skills span Python, Java, Docker, Kubernetes, and Azure DevOps, and she has gained international experience through roles in Luxembourg, Canada, France, and Tunisia. Passionate about both academic and applied innovation, she has contributed to multiple interdisciplinary projects in AI, human-computer interaction, and intelligent systems. Rania is also active in professional communities such as IEEE and youth science associations, reflecting her commitment to collaborative growth and scientific outreach.

Professional Profile 

🎓 Education Background

Rania Hamdani has a strong academic foundation rooted in engineering and scientific rigor. She earned her Engineering Degree in Software Engineering from the National Higher School of Engineers of Tunis (ENSIT) between 2021 and 2024, where she specialized in Advanced Design, Service-Oriented Architecture, Object-Oriented Programming, Database Management, and Operational Research. Prior to that, she completed a Preparatory Cycle for Engineering Studies at the Preparatory Institute for Engineering Studies of Tunis (2019–2021), focusing intensively on mathematics, physics, and core technology subjects—a rigorous program designed to prepare students for elite engineering schools. Rania also holds a Baccalaureate in Mathematics from Pioneer High School Bourguiba Tunis, where she graduated with distinction (Very Good) in 2019. This academic journey has laid a solid foundation for her multidisciplinary research and professional growth in software and data sciences.

💼 Professional Experience 

Rania Hamdani has developed a rich and diverse professional portfolio across academia and industry, with hands-on experience in software engineering, research, and cloud-based technologies. She is currently a Research Scientist at the University of Luxembourg (since November 2024), where she focuses on optimizing decision-making processes in cloud environments through advanced data integration techniques. Prior to this, she served as a Research Intern at the same institution (May to October 2024), contributing to projects in Ontology-Driven Knowledge Management and Cloud-Edge AI, resulting in three published papers. Alongside her academic work, Rania worked as a Part-Time Software Engineer at CareerBoosts in Canada (2021–2025), where she honed her skills in DevOps, data analysis, test automation, and backend development using tools like Python, Docker, and Kubernetes. Her earlier internships include roles at Qodexia (France), Sagemcom (Tunisia), and Tunisie Telecom, where she worked on smart recruitment platforms, employee management systems, and server monitoring tools using full-stack technologies such as SpringBoot, Angular, and PostgreSQL. This blend of research and industry experience positions Rania as a versatile and forward-thinking technology professional.

🔬 Research Interests of Rania Hamdani

Rania Hamdani’s research interests lie at the intersection of software engineering, operational research, data integration, and cloud-edge intelligence, with a strong orientation toward Industry 5.0 applications. She is particularly passionate about developing intelligent systems that enhance decision-making in cloud-based and distributed environments, leveraging AI, machine learning, and ontology-driven knowledge frameworks. Her work focuses on enabling seamless management of heterogeneous data sources, scalable architectures, and adaptive human-computer interaction (HCI) systems. Rania is also deeply engaged in exploring Cloud-Edge AI ecosystems, recommender systems, and automation pipelines using modern tools like Docker, Kubernetes, TensorFlow, and Neo4j. Her multidisciplinary approach reflects a vision for integrating research-driven insights with real-world industrial challenges, making her contributions both academically valuable and practically impactful.

🏅 Awards and Honors of Rania Hamdani

While still in the early stages of her research career, Rania Hamdani has demonstrated exceptional academic and technical promise. She graduated with a “Very Good” distinction in her Baccalaureate in Mathematics from the prestigious Pioneer High School Bourguiba in Tunis, reflecting her consistent academic excellence. Rania has also earned multiple professional certifications from Microsoft, including Azure Fundamentals, Azure Data Fundamentals, Azure AI Fundamentals, and Azure Security, Compliance, and Identity Fundamentals, showcasing her dedication to staying at the forefront of cloud and AI technologies. Though formal research awards or honors are not yet listed, her early publications, research contributions, and international internships highlight a trajectory poised for future recognition in both academic and industry spheres.

Publications Top Noted

Title: Adaptive human‑computer interaction for Industry 5.0: A novel concept, with comprehensive review and empirical validation
Authors: Rania Hamdani, Inès Chihi
Year: 2025
Journal: Computers in Industry (Volume 168)
DOI: 10.1016/j.compind.2025.104268

🧾 Conclusion

Rania Hamdani is highly suitable for the Best Emerging Researcher or Young Researcher Award category. She has excellent technical skills, promising early-stage research output, international exposure, and a forward-looking vision in areas like Industry 5.0, cloud-edge intelligence, and AI-based decision systems. While still building her publication track record and academic leadership, her current trajectory shows strong promise for future impactful contributions to scientific and industrial domains.

 

 

Jerzy Montusiewicz | Computer Science and Artificial Intelligence | Best Researcher Award

Jerzy Montusiewicz | Computer Science and Artificial Intelligence | Best Researcher Award

Mr Jerzy Montusiewicz, Lublin University of Technology, Department of Computer Science, Poland

Based on the research achievements of Prof. Jerzy Montusiewicz, he appears to be a strong candidate for the Best Researcher Award. Here’s a summary of his contributions and achievements:

Publication profile

google scholar

Research Summary for Best Researcher Award

1. K-medoids Clustering and Fuzzy Sets for Isolation Forest
Montusiewicz co-authored this 2021 IEEE International Conference on Fuzzy Systems paper on clustering and fuzzy sets, highlighting advanced methodologies in data analysis. This work is cited for its impact on clustering techniques in complex datasets.

2. Preparation of 3D Models of Cultural Heritage Objects to be Recognized by Touch by the Blind—Case Studies
In this 2022 Applied Sciences publication, Montusiewicz contributed to developing 3D models of cultural heritage objects accessible to the visually impaired, showcasing his commitment to inclusivity in digital heritage.

3. Comparative Analysis of Digital Models of Objects of Cultural Heritage Obtained by the “3D SLS” and “SfM” Methods
This 2021 study, published in Applied Sciences, explores the comparative effectiveness of different 3D scanning methods for cultural heritage preservation, reflecting Montusiewicz’s expertise in digital preservation techniques.

4. 3D Scanning and Visualization of Large Monuments of Timurid Architecture in Central Asia—A Methodical Approach
Montusiewicz’s 2020 Journal on Computing and Cultural Heritage article demonstrates innovative methods for scanning large historical monuments, emphasizing his contributions to preserving Central Asian architectural heritage.

5. Virtual and Interactive Museum of Archaeological Artefacts from Afrasiyab—An Ancient City on the Silk Road
This 2020 paper in Digital Applications in Archaeology and Cultural Heritage presents the creation of a virtual museum for archaeological artefacts, illustrating Montusiewicz’s role in advancing digital tools for archaeology.

6. A Decomposition Strategy for Multicriteria Optimization with Application to Machine Tool Design
Montusiewicz’s 1990 publication in Engineering Costs and Production Economics addresses optimization strategies in machine tool design, demonstrating his early contributions to engineering and optimization techniques.

7. Structured-Light 3D Scanning of Exhibited Historical Clothing—A First-Ever Methodical Trial and Its Results
This 2021 Heritage Science study, co-authored by Montusiewicz, represents a pioneering effort in 3D scanning of historical clothing, marking a significant advancement in the field of heritage science.

8. Documenting the Geometry of Large Architectural Monuments Using 3D Scanning—The Case of the Dome of the Golden Mosque of the Tillya-Kori Madrasah in Samarkand
Montusiewicz’s research, published in 2022, focuses on documenting the geometry of significant architectural monuments, highlighting his continued impact on architectural preservation through advanced scanning techniques.

Prof. Montusiewicz’s diverse research, spanning from advanced 3D scanning techniques to the preservation of cultural heritage, underscores his significant contributions to the fields of computer graphics and digital preservation. His innovative approaches and practical applications make him an exemplary candidate for the Best Researcher Award.

Research focus

Based on the provided publications, the research focus appears to be in digital heritage preservation and 3D scanning technologies. The work of J. Montusiewicz and collaborators emphasizes creating and analyzing 3D models of cultural heritage objects, including methods for blind accessibility and the application of scanning technologies for historical artifacts and architecture. This includes comparative studies of different scanning methods and their effectiveness, as well as the development of interactive digital museums. Their research contributes significantly to both the preservation of cultural heritage and the advancement of technological applications in archaeology. 🏛️🔍📏

Publication top notes

K-medoids clustering and fuzzy sets for isolation forest

Preparation of 3D models of cultural heritage objects to be recognised by touch by the blind—case studies

Comparative analysis of digital models of objects of cultural heritage obtained by the “3D SLS” and “SfM” methods

3D Scanning and Visualization of Large Monuments of Timurid Architecture in Central Asia–A Methodical Approach

Virtual and interactive museum of archaeological artefacts from Afrasiyab–an ancient city on the silk road

A decomposition strategy for multicriteria optimization with application to machine tool design

Structured-light 3D scanning of exhibited historical clothing—a first-ever methodical trial and its results