My research focuses on developing digital twins to support space mission’s lifecycle, from early trade studies to operations. Rather than treating simulation as a purely offline activity, I work on twin architectures that remain “alive”: they ingest new data from the physical system, update their internal state, and return actionable feedback to improve performance and reduce operational risk.

The main area of my work is a digital twin of the optical imaging chain for orbiting satellites: spanning acquisition planning, sensor modelling, scene rendering, and synthetic image analysis. This includes building custom high-fidelity 3D world environments from mission-relevant inputs, as well as developing simulated acquisition pipelines to reproduce realistic satellite camera products under controlled conditions.

I am currently developing this framework within an Earth Observation use case, with the goal of closing the loop between imaging operations and data exploitation. In this scenario, the emphasis is on the end-to-end workflow that helps anticipate how orbital geometry, attitude, illumination, and atmospheric conditions translate into the final data products and their usability during the mission design phase. I am now working on the connection of the synthetic pipeline to real mission data. In particular, I am designing ingestion workflows that combine ephemerides, telemetry, and external context, into a state vector describing orbit, attitude, acquisition settings, and environmental conditions. Based on this evolving state, the twin is intended to perform visibility and illumination assessments, predict image quality, and produce ready-to-use masked datasets for training and testing analysis algorithms based on machine learning. These outputs enable an operational feedback loop, supporting recommendations on acquisition strategy, imaging-parameter tuning, and repointing priorities.

At the Space It Up! Days, I presented the ongoing work of my Spoke on STAR (Space mission Twin for Architecture Representation), a modular mission-level digital twin framework designed to represent multiple satellite subsystems within a single, coherent environment. Within STAR, my contribution is the observation module, which builds on my research. In parallel, STAR integrates complementary modules addressing key mission functions, such as the health monitoring of critical elements, multi-fidelity structural environment interaction, and operational support for conjunction assessment and collision-avoidance decision making. The framework is currently under active development, with a strong emphasis on consolidating the interconnections among modules and delivering a unified user interface. In addition to advancing the observation module, I support the coordination of the joint effort; therefore, at the event I acted as the contact point for STAR Poster, alongside the presentation of my specific research results in the same context.

Overall, my objective is to provide a rigorous, data-driven digital counterpart of the physical assets, that supports both design-phase “what-if” studies and operational decision making, enhancing the connectivity between models and real-world operations.

Click here for more information and here to view my poster.