Research Assistant | INaB – Institute of Sustainability in Civil Engineering RWTH Aachen | Germany
Manouchehr Shokri is a Research Assistant at the Institute for Sustainability in Civil Engineering at RWTH Aachen University, specializing in life cycle sustainability assessment and advanced infrastructure engineering. With a strong academic foundation in civil engineering, transportation, and highway systems, he has contributed to significant research initiatives in structural mechanics, railway infrastructure design, and sustainable road and waterway systems. His professional experience includes leadership roles in construction management and technical office supervision, along with extensive research involvement in developing sustainability assessment frameworks, conducting life cycle analyses for asphalt pavements, hydraulic structures, and innovative rehabilitation solutions aligned with international standards. His scholarly work spans environmental impact assessment, sustainable materials, geosynthetics, renewable energy integration, seismic damage prediction, and data-driven modeling, reflected through high-quality publications and interdisciplinary collaborations. He also contributes to the academic community through editorial engagements, peer review activities, and professional memberships supporting advancements in sustainable infrastructure. His research impact includes 506 citations, 17 publications, and an h-index of 10.
Featured Publications
1. Manouchehr Shokri, Band S.S., Janizadeh S., Chandra Pal S., Saha A., Chakrabortty R., Novel ensemble approach of deep learning neural network (DLNN) model and particle swarm optimization (PSO) algorithm for prediction of gully erosion susceptibility. Sensors, 2020.
2. Shokri M., Mankaa R.N., Traverso M., Geo-environmental analysis and mechanical properties of geosynthetics in railway components industry (Sub and Superstructures). Journal of Cleaner Production, 2025.
3. Meiabadi M.S., Moradi M., Karamimoghadam M., Ardabili S., Bodaghi M., Shokri M., Modeling the producibility of 3D printing in polylactic acid using artificial neural networks and fused filament fabrication. Polymers, 2021.
4. Shokri M., Tavakoli K., A review on the artificial neural network approach to analysis and prediction of seismic damage in infrastructure. International Journal of Hydromechatronics, 2019.
5. Mosavi A., Qasem S.N., Shokri M., Band S.S., Mohammadzadeh A., Fractional-order fuzzy control approach for photovoltaic/battery systems under unknown dynamics, variable irradiation and temperature. Electronics, 2020.
Manouchehr Shokri’s work advances sustainable infrastructure by integrating rigorous life cycle assessment with innovative engineering approaches that reduce environmental burdens and enhance long-term performance. Through his contributions, he strengthens global efforts toward environmentally responsible, resilient, and future-ready infrastructure systems.