Antonio Moricca

R&D engineer within the tuning team. I act as a bridge between engineering and data science. Currently, resident engineer in Renault Technical Center in Lardy for a partnership between Renault and Dumarey to develop a 2.0 l Euro7 diesel engine Main activities and contributions: - Development and optimization of advanced control strategies for combustion and air systems, leveraging Python, machine learning (ML), and time series modeling techniques. - Designed a virtual turbocharger time-response model using an ensemble of LSTM neural networks and XGBoost, integrated with a closed-loop controller to enable offline tuning and significantly reduce testing time. -Introduced innovative calibration procedures for combustion warm-up, applying multi-objective optimization (Pareto front analysis) to jointly optimize enthalpy and temperature, reducing warm-up time and NOx emissions. - Developed neural network-based tools for global Design of Experiments (DOE) modeling, optimized via genetic algorithms, improving prediction accuracy for key emissions (soot, hydrocarbons). -Designed and implemented a custom calibration management software (Python, PyQt6) to handle A2L and HEX files, improving efficiency and achieving significant license cost savings. -Actively contributed to innovation initiatives by integrating automation tools into the traditional R&D calibration workflow, to speed-up and standardise dayly tasks.

Calibration engineer with focus on combustion to meet performance and emission requirements. The main project has been the development of 3.0 l diesel engine of General Motors for the US market.