Luca Battaglia

Luca Battaglia holds a Master’s degree in Mechanical Engineering from the University of Trieste (Italy) and is currently part of the Application Engineering team at ESTECO S.p.A.

His work sits at the intersection of machine learning, numerical optimization, and engineering applications. He focuses on developing and integrating data-driven models into multi-disciplinary optimization workflows, enabling more efficient and scalable design processes. His activities include data analysis, surrogate modeling, reduced-order modeling (ROM), and the application of machine learning techniques to complex engineering problems.

Luca is involved across the full lifecycle of data-driven solutions, from model development and validation to their integration and deployment in production environments. He contributes to ensuring that predictive models are robust, reliable, and effectively embedded within existing engineering workflows and software platforms.

In his role, Luca collaborates closely with customers across different industries, providing technical consulting, workflow design, and training during both pre-sale and post-sale phases, supporting the adoption of advanced optimization and machine learning-driven solutions.

Since 2018, Luca has been actively involved in several European Union and regional research projects, including H2020 GASVESSEL and ARIA. In the GASVESSEL project, aimed at demonstrating the techno-economic viability of an innovative compressed natural gas transportation system, he contributed to the simulation and optimization of lightweight composite pressure cylinders and to the identification of optimal shipping strategies. In the ARIA project, he worked on the development of an Uncertainty Quantification methodology based on Snapshot Proper Orthogonal Decomposition (POD) Reduced Order Models and Polynomial Chaos Expansion (PCE), enabling efficient analysis of complex systems while reducing computational costs.