Meriem Seguini – Structural Health Monitoring – Women Researcher Award

Meriem Seguini - Structural Health Monitoring - Women Researcher Award

Civil Engineering at University of Science and technology of Oran USTOMB

Engaged in advanced research in civil engineering, this academic has consistently contributed to structural stability, geotechnical engineering, and computational modeling. A vital member of the Laboratory of Applied Mechanics, the work spans soil-structure interaction, nonlinear analysis, and machine learning for structural health monitoring. Involvement in multiple international conferences and scientific committees reflects commitment to global academic collaboration. Teaching and supervising responsibilities at the University of Sciences and Technology of Oran highlight a strong dedication to higher education. This well-rounded profile merges theoretical and applied knowledge across academia, research, and industry-focused solutions in civil and structural engineering.

Professional Profile

ORCID | Scopus

Education

Educational achievements began with a Bachelor's in Civil Engineering, followed by a Master’s in Civil and Industrial Constructions, both from the University of Sciences and Technology of Oran Mohamed Boudiaf. Academic progression culminated in a PhD focused on Construction and Stability of Structures, fostering expertise in geotechnics and mechanics. The path to associate professorship was achieved in 2021. Formal training was enriched through international exposure, including doctoral research at EPFL, Lausanne. Degree equivalency recognition from Naric (Belgium) further reflects academic standards. This foundation in structural engineering and computational mechanics supports the ongoing research trajectory.

Professional Experience

Meriem Seguini has held academic positions since 2012, evolving from assistant professor to associate professor at USTO-MB. Responsibilities include course instruction, supervising research, and coordinating international sessions on structural health and damage detection. Her practical experience includes internships in Swiss labs and construction firms in Algeria, enhancing her applied understanding of energy geostructures and seismic analysis. Chairing sessions in key international conferences across Europe and Asia showcases leadership and professional networking. Contributions to technical training and the scientific committee work emphasize the impact on global geotechnical and structural research communities.

Research Interest

Specialization lies in the nonlinear behavior of soil-structure systems, dynamic analysis of geostructures, and advanced modeling techniques using finite elements. Interests extend to the integration of artificial intelligence and machine learning in predicting structural anomalies, especially within pipelines and buried systems. Meriem Seguini focuses on stochastic modeling, spatial variability of soil, and sustainable infrastructure analysis. Experimental vibration analyses combined with computational simulations form a core of her applied research. The work addresses challenges in civil engineering reliability and resilience, bridging the gap between theoretical advancement and practical infrastructure safety.

Award And Honor

Recognition as chair and scientific committee member in numerous international conferences such as ICSCES and FFW underscores professional credibility. Meriem Seguini was awarded the equivalence of her PhD in Belgium, acknowledging the international standard of her academic work. Selected to present at key platforms across Europe and Asia, her research contributions are well regarded in structural engineering circles. Engagements at EPFL and Ghent University reflect the value attributed to her collaboration and academic excellence. These honors mark a trajectory of distinction and influence in civil and structural engineering fields.

Research Skill

Competence includes proficiency in tools such as Abaqus, Matlab, SAP2000, and Comsol for simulation and analysis. A strong command of finite element methods supports research in complex nonlinear systems. Skills extend to dynamic and probabilistic modeling, thermal and mechanical simulations of buried structures, and seismic analysis. Meriem Seguini integrates artificial neural networks with structural diagnostics, applying hybrid AI techniques for damage prediction. Additional capabilities in programming, visualization, and engineering graphics reinforce analytical strength. Effective communication in Arabic, French, English, and intermediate German further enhances global research dissemination and collaboration potential.

Publications

Research output includes over a dozen peer-reviewed papers in prestigious journals and international conferences. Key topics span nonlinear beam analysis, soil spatial variability, and AI-based damage detection. Publications in journals like Periodica Polytechnica and Arabian Journal for Science and Engineering reflect high-impact contributions. Several works have introduced innovative modeling using Monte Carlo methods and artificial neural networks. Co-authored publications with global researchers signify interdisciplinary collaboration. Meriem Seguini’s publications provide critical insights into improving civil structure reliability using modern computational tools and predictive modeling techniques across international engineering platforms.

Title: Forecasting and characterization of composite pipeline based on experimental modal analysis and YUKI-gradient boosting
Authors: M. Seguini, S. Khatir, D. Boutchicha, A. Ould Brahim, B. Benaissa, C. Le Thanh, M. Noori, N. Fantuzzi
Journal: Construction and Building Materials (2024-04)

Title: Structural mechanics [A probabilistic study of nonlinear behavior in beams resting on tensionless soil with geometric considerations]
Authors: Seguini Meriem, Nedjar Djamel
Journal: HCMCOU Journal of Science – Advances in Computational Structures (2024-02-05)

Title: Crack Identification in Pipe Using Improved Artificial Neural Network
Authors: Meriem Seguini, Tawfiq Khatir, Samir Khatir, Djilali Boutchicha, Nedjar Djamel, Magd Abdel Wahab
Journal: Lecture Notes in Mechanical Engineering (2023)

Title: Machine Learning for Predicting Pipeline Displacements Based on Soil Rigidity
Authors: Meriem Seguini, Samir Khatir, Djamel Nedjar, Magd Abdel Wahab
Journal: Proceedings of the 10th International Conference on Fracture Fatigue and Wear (2023)

Title: Crack prediction in pipeline using ANN-PSO based on numerical and experimental modal analysis
Authors: Meriem Seguini, Samir Khatir, Djilali Boutchicha, Djamel Nedjar, Magd Abdel Wahab
Journal: Smart Structures and Systems (2021)

Title: Experimental and Numerical Vibration Analyses of Healthy and Cracked Pipes
Authors: Meriem Seguini, Djilali Boutchicha, Samir Khatir, Djamel Nedjar, Cuong-Le Thanh, Magd Abdel Wahab
Journal: Lecture Notes in Civil Engineering (2021)

Conclusion

Meriem Seguini’s academic journey and research excellence reflect a career deeply rooted in innovation, teaching, and global collaboration. From experimental fieldwork to high-end computational simulation, the body of work demonstrates a commitment to engineering progress. Contributions in AI-integrated structural diagnostics and nonlinear analysis establish a foundation for future breakthroughs in infrastructure safety. Educational leadership and international conference participation reinforce influence beyond regional boundaries. With a multidisciplinary approach and evolving skill set, continued impact in civil and structural engineering is assured. The trajectory remains aligned with sustainable development and advanced research frontiers.

Hanine Merzougui – Structural Health Monitoring – Best Researcher Award

Hanine Merzougui - Structural Health Monitoring - Best Researcher Award

Batna 2 University - Algeria

AUTHOR PROFILE

ORCID

AI ENGINEER & DATA ANALYST 🤖

Hanine Merzougui is a highly motivated AI Engineer and Data Analyst from Batna 2 University, with expertise in a variety of programming languages including Python, R, Java, and C++. Her research focuses on the application of artificial intelligence technologies such as Machine Learning, Deep Learning, Natural Language Processing, and Computer Vision to enhance human life. Hanine is fluent in Arabic, French, and English, and is passionate about creating innovative AI tools, like the GptStoryTeller, which showcases her commitment to advancing technology for societal benefits.

TEACHING EXPERIENCE 📚

As a teaching assistant at Batna 2 University, Hanine has played a pivotal role in educating future engineers and computer scientists. She has been responsible for conducting lab sessions, guiding projects, and evaluating practical work for both Bachelor's seniors and sophomore engineers. Her dedication to mentoring students highlights her commitment to fostering an engaging and supportive learning environment. Hanine's hands-on approach and her ability to simplify complex concepts have made her a valuable asset to her department.

SOFTWARE DEVELOPMENT 💻

During her tenure as a software developer at Middle School Bensaadallah Belkhir, Hanine developed a management software that streamlined student activity tracking. This project not only honed her programming skills but also gave her insight into practical applications of technology in education. Her proficiency in Java and understanding of user needs allowed her to create a tool that significantly improved the management of student activities.

RESEARCH AND INNOVATION 🔍

Hanine’s research is centered around the digitalization and automation of approval processes for durum wheat grain quality in Algeria, utilizing computer vision and machine learning. Her thesis project focused on enhancing quality control through innovative AI applications, demonstrating her ability to combine theoretical knowledge with practical solutions. By publishing her findings, Hanine contributes to the academic community and the broader agricultural sector, paving the way for advancements in food quality assessment.

CONFERENCES & SEMINARS 🎤

Hanine actively participates in conferences and seminars, sharing her research and insights with peers and experts. Her presentations on the use of deep learning approaches for durum wheat seed certification and quality approval have garnered attention in the academic community. By engaging with fellow researchers, Hanine not only disseminates knowledge but also fosters collaborations that can lead to groundbreaking advancements in her field.

HONORS AND CERTIFICATIONS 🏆

Recognized for her contributions, Hanine has received several accolades, including a Startup Certificate Patent for her master's thesis and a Certificate of Appreciation from the GDG Batna Hackathon for developing an innovative AI storytelling tool. Additionally, she earned the Google Data Analytics Professional Certificate, showcasing her skills in data preparation, analysis, and visualization. These achievements reflect her commitment to continuous learning and excellence in her field.

DIGITAL SKILLS & COMPETENCIES 💡

Hanine possesses a robust set of digital skills, including proficiency in machine learning frameworks such as TensorFlow and Keras, along with expertise in data management using SQL and MySQL. Her programming background encompasses a variety of languages, and she has a strong foundation in statistical analysis and data visualization. Hanine’s ability to leverage technology effectively positions her as a leading figure in the field of AI and data analytics.

NOTABLE PUBLICATION

Title: Skin Cancer Diagnosis Using VGG16 and Transfer Learning: Analyzing the Effects of Data Quality over Quantity on Model Efficiency
Authors: [Author names not provided in the given information]
Year: 2024