Three pillars: Astrodynamics, Deep Learning & AI, and Design–Build–Test.
Artemis-era mission design, computer-vision navigation, and hands-on hardware.
What, how and why? Space exploration is entering a new operational era: the Artemis program is returning humans to the Moon, and commercial ventures are rewriting the economics of cislunar logistics. My work sits at the intersection of these forces — designing mission architectures through Generative AI and Explainable AI, building computer vision navigation systems for spacecraft rendezvous, and contributing to the hardware systems that make it all real. The following pillars define my technical expertise.
Astrodynamics
The motion of natural and artificial objects in space — from preliminary orbit determination for Brazilian satellites to Artemis-era mission architectures in the CR3BP.
- Interplanetary trajectory design
- Rendezvous & Proximity Operations
- Computer vision-based navigation
- Multi-body dynamics & CR3BP
- In-situ resource utilization
Deep Learning & AI
Generative design of space systems via Reinforcement Learning, Explainable AI for mission architecture trade-offs, and neural networks for spacecraft navigation and transfer optimization.
- Reinforcement Learning for design
- Explainable AI (XAI)
- Generative Design & System-of-Systems
- Computer Vision & SE(3) Dynamics
- Deep Learning Mission Design
Design, Build & Test
Hands-on engineering: carbon-fiber rocket structures with Project Jupiter, LIDAR-drone integration for Mars EDL research at MDRS, and the RocketPy flight simulator.
- Topological optimization
- Multi-physics modeling
- Design space exploration
- Additive manufacturing
- Industry 4.0