// Geotechnical Engineer & Researcher | Infrastructure, Soil Mechanics & AI
Geotechnical engineer and researcher at Deltares with over 10 years of experience across geotechnical engineering, site investigation, monitoring, natural hazards and applied research. His work combines a strong geotechnical foundation with AI and data methods, from CPT based subsurface schematisation and machine learning to field investigation, laboratory testing and fibre optic monitoring, alongside slope and embankment stability and probabilistic landslide assessment. Across research and consultancy projects, he turns complex geotechnical data into clearer engineering decisions.
// experience
// education
Thesis: Deep Learning for Geotechnical Engineering: The Effectiveness of Generative Adversarial Networks in Subsoil Schematization.
Delft University of Technology, Netherlands
International Geotechnical Centre
Thesis: Geomechanical characterisation and slope stability of a soil and municipal solid waste system at the San Ramón landfill.
// Honorable MentionUniversity of Costa Rica
University of Costa Rica
// distinctions
Schreuders Study Prize
Honorable Mention — MSc thesis on deep learning for geotechnical subsurface schematisation.
Cum Laude
Diploma in Underground and Overground Geomechanics, International Geotechnical Centre.
Honorable Mention
MSc in Engineering Geology thesis, University of Costa Rica.
// selected publications
Assessment of critical train speeds of railways on soft soils – a case study
E3S Web of Conferences, 730, 05001.
doi.org/10.1051/e3sconf/202673005001Application of line loads versus block loads for railway embankment stability assessment
International Conference on Advances and Innovations in Soft Soil Engineering, 24–26 August 2026, Delft.
SchemaGAN: A conditional generative adversarial network for geotechnical subsurface schematisation
Computers and Geotechnics, 183, 107177.
doi.org/10.1016/j.compgeo.2025.107177GEOSYN: Synthetic geotechnical cross-sections for machine learning applications
29th European Young Geotechnical Engineers Conference.
doi.org/10.32762/eygec.2025.23Optimizing geotechnical in-situ site investigations using Deep Reinforcement Learning
Geodata and AI, 100038.
doi.org/10.1016/j.geoai.2025.100038Application of kinematic admissibility analysis and limit equilibrium to optimize the excavation geometry of a quarry in the canton of León Cortés, San José, Costa Rica
Revista Geológica de América Central, 1–25.
doi.org/10.15517/rgac.v66i0.49786// skills
// site investigation & geodata
// laboratory & soil mechanics
// monitoring & instrumentation
// AI & data methods
// numerical & analytical geotechnics
// software & reproducibility
// natural hazards & risk
// languages
// contact
Open to discussing research, engineering projects and collaboration in geotechnical engineering and infrastructure.