Mais Mayassah | Machine Learning Applications | Research Excellence Award

Ms. Mais Mayassah | Machine Learning Applications | Research Excellence Award

Structural and Geotechnical Engineering Department, Szechenyi Istvan University, Gyor, Hungary | Hungary

Ms. Mais Mayassah is a dedicated Water and Geotechnical Engineer and PhD researcher at Széchenyi István University, Hungary, specializing in structural engineering, geotechnics, and hydraulic systems. With extensive academic and professional experience, she has contributed to advanced research within the National Laboratory for Water Science and Water Security, focusing on flood resilience, levee safety, and climate-driven hydrological challenges. Her background includes roles as a civil engineer and consultant in Syria, where she supervised infrastructure, sanitation, and construction projects, alongside years of university teaching in hydraulics and building materials. Her research integrates numerical modeling, artificial intelligence, and geotechnical analysis to develop innovative, data-driven solutions for sustainable and resilient water infrastructure systems.

Citation Metrics (Scopus)

30
20
10
5
0

Citations
12

Documents
4

h-index
1

Citations

Documents

h-index


View Scopus Profile

Featured Publications

Duc Cong Nguyen | Machine Learning and AI Applications | Best Researcher Award

Mr. Duc Cong Nguyen | Machine Learning and AI Applications | Best Researcher Award

Mr. Duc Cong Nguyen at Silesian University of Technology, Poland

👨‍🎓 Profiles

Orcid Profile
Scopus Profile
Google Scholar Profile
Research Gate Profile

🧑‍🎓 Duc Cong Nguyen: PhD Student and Structural Health Monitoring Specialist

📚 Education

  • PhD Student (2020 – 2024)
    Silesian University of Technology, Faculty of Civil Engineering, Gliwice, Poland
    (Supported by NAWA Polish government and Vietnamese government)

🔬 Professional Experience

  • PhD Research: Developing and applying vibration-based structural health monitoring (SHM) techniques for railway steel arch bridges using advanced AI models and signal processing methods.
  • Consultancy: Contributing to SHM projects for the Dębica railway steel arch bridge in Poland.
  • Previous Experience: Over a decade of expertise in bridge structural testing and pile testing in Vietnam.

🔍 Research Interests

  • AI and Machine Learning 🤖
  • Structural Health Monitoring (SHM) 🏗️
  • Bridges and Railway Bridges 🚉
  • Vibration Measurement and Diagnostic Load Testing 📏

💡 Key Contributions

  • Innovated advanced signal processing techniques for SHM, including wavelet transforms and FFT algorithms.
  • Developed GoogLeNet CNN models for classification and pattern recognition of bridge vibration signals.
  • Conducted analyses of historical dynamic responses using FFT techniques to estimate tension forces in bridge components.

📖 Publications

Structural Health Monitoring for Dębica Railway Steel Arch Bridge in Poland
    • Authors: Duc Cong Nguyen, Marek Salamak, Andrzej Katunin, Grzegorz Poprawa
    • Journal: Civil and Environmental Engineering Reports
    • Year: 2024
Vibration-based SHM of Railway Steel Arch Bridge with Orbit-Shaped Image and Wavelet-Integrated CNN Classification
    • Authors: Duc Cong Nguyen, Marek Salamak, Andrzej Katunin, Grzegorz Poprawa, Michael Gerges
    • Journal: Engineering Structures
    • Year: 2024
Vibration-based SHM of Dębica Railway Steel Bridge with Optimized ANN and ANFIS
    • Authors: Duc Cong Nguyen, Marek Salamak, Andrzej Katunin, Grzegorz Poprawa, Piotr Przystałka, Mateusz Hypki
    • Journal: Journal of Constructional Steel Research
    • Year: 2024
Finite Element Model Updating of Steel Bridge Structure Using Vibration-Based Structural Health Monitoring System: A Case Study of Railway Steel Arch Bridge in Poland
    • Authors: Duc Cong Nguyen, Marek Salamak, Andrzej Katunin, Grzegorz Poprawa
    • Journal: Experimental Vibration Analysis for Civil Engineering Structures: EVACES. Lecture Notes in Civil Engineering (433)
    • Year: 2023