معرفی
Marco Previtali is a Researcher in Civil Engineering specializing in geotechnical engineering with an active publication record of 47 research outputs. His work spans computational modeling, experimental testing, and practical applications in rock mechanics and foundation engineering, primarily affiliated with an unspecified university department.
Previtali completed his PhD in 2023 with a thesis on “Experimental and numerical characterization of Double-Twisted hexagonal meshes for rockfall protection” under supervisors M. Ciantia, S. Spadea, G.B. Crosta, and R.P. Castellanza. His doctoral research established foundations in numerical simulation of geotechnical structures.
His core research integrates Discrete Element Method (DEM) with advanced computational techniques to address challenges in soft rock mechanics, pile foundation design, and offshore renewable energy infrastructure. Previtali’s work emphasizes numerical modeling of large deformations, particle-based simulations, and AI-driven geotechnical solutions, with significant contributions to understanding screw pile interactions, chalk behavior, and porous rock mechanics. Current trends show increasing focus on 4D modeling and AI integration for predictive geotechnical analysis.
Recent publications (2024–2026) reveal a strategic shift toward hybrid computational approaches, combining DEM with machine learning to solve complex soil-structure interaction problems. His research bridges theoretical modeling and practical engineering applications, particularly in offshore wind energy foundations and challenging soil conditions, while maintaining strong international collaborations across Europe.
No scientific awards or honors are documented in the available information.
Previtali maintains an extensive collaborative network evidenced by co-authorship on 47 publications since 2019, with notable partnerships in offshore geotechnics and numerical modeling. His research trajectory indicates growing leadership in AI-geotechnics integration, though specific grant details or student supervision beyond his own PhD are not disclosed. The publication surge (16 outputs in 2024) suggests active involvement in major research initiatives.
While explicit lab affiliations are unconfirmed, his experimental work on 4D model testing and particle-scale simulations implies access to advanced geotechnical laboratories with capabilities for small-scale physical modeling and high-performance computational resources.
