Solid expertise in Computational Fluid Dynamic models applied to ship design and optimization, with particular focus on resistance and seakeeping predictions of high speed unconventional vessels specially trimaran ships. Strong ability in the development of automatic procedures for hull form generation, fluid dynamic, solid mechanic analysis, and stability verification ultimately aimed at design optimization. Extensive experience in applying machine learning techniques for construction of surrogate models suitable for cost-effective multi-disciplinary optimization in highly multi­dimensional, design space. Proven ability in the development of Set-Based Design frameworks based on Risk-Adaptive surrogate models constructed from simulation data coming from different fidelity information sources. Significant experience in parallel high performance computing. Demonstrated ability in collaborating with diverse multi-institutional research teams. Implementation of ship spiral design from concept design to preparation detail and shop design plans. More than six years job experience in design and building steel, aluminum, and fiberglass marine vehicles